{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b3a7a0d0",
   "metadata": {},
   "source": [
    "属性  | 定义 \n",
    "------|------\n",
    "Year built range | 住宅建成年份  \n",
    "Assessed value range  | 住宅价值     \n",
    "Number of stories  | 住宅楼层数  \n",
    "Square footage range  | 住宅占地面积      \n",
    "Number of bedrooms  | 卧室个数      \n",
    "Total number of bathrooms  | 浴室个数 \n",
    "Number of kitchens  | 厨房个数\n",
    "Number of fireplaces  | 壁炉个数\n",
    "Number of occupants  | 住户个数\n",
    "Median income range  | 收入\n",
    "Average annual electric use (kWh)  | 年均用电量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 355,
   "id": "711de5b4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "from sklearn.model_selection import train_test_split, GridSearchCV\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.feature_selection import SelectPercentile, f_classif\n",
    "from sklearn.tree import DecisionTreeClassifier, plot_tree\n",
    "from sklearn.metrics import accuracy_score, roc_auc_score, f1_score, roc_curve, r2_score,mean_squared_error, recall_score\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "pd.set_option('mode.chained_assignment',None)\n",
    "plt.rcParams['font.sans-serif'] = ['Microsoft JhengHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69aa5056",
   "metadata": {},
   "source": [
    "读取数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 356,
   "id": "9127764c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(55143, 11)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year built range</th>\n",
       "      <th>Assessed value range</th>\n",
       "      <th>Number of stories</th>\n",
       "      <th>Square footage range</th>\n",
       "      <th>Number of bedrooms</th>\n",
       "      <th>Total number of bathrooms</th>\n",
       "      <th>Number of kitchens</th>\n",
       "      <th>Number of fireplaces</th>\n",
       "      <th>Number of occupants</th>\n",
       "      <th>Median income range</th>\n",
       "      <th>Average annual electric use (kWh)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>$100k - $150k</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 1,500</td>\n",
       "      <td>1 or 2</td>\n",
       "      <td>1 or 1.5</td>\n",
       "      <td>1 or less</td>\n",
       "      <td>0</td>\n",
       "      <td>3 or 4 occupants</td>\n",
       "      <td>$50k - $100k</td>\n",
       "      <td>4309.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 1,500</td>\n",
       "      <td>1 or 2</td>\n",
       "      <td>1 or 1.5</td>\n",
       "      <td>1 or less</td>\n",
       "      <td>0</td>\n",
       "      <td>3 or 4 occupants</td>\n",
       "      <td>$50k - $100k</td>\n",
       "      <td>3218.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 1,500</td>\n",
       "      <td>1 or 2</td>\n",
       "      <td>1 or 1.5</td>\n",
       "      <td>1 or less</td>\n",
       "      <td>0</td>\n",
       "      <td>3 or 4 occupants</td>\n",
       "      <td>$50k - $100k</td>\n",
       "      <td>6938.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 1,500</td>\n",
       "      <td>1 or 2</td>\n",
       "      <td>1 or 1.5</td>\n",
       "      <td>1 or less</td>\n",
       "      <td>0</td>\n",
       "      <td>3 or 4 occupants</td>\n",
       "      <td>$50k - $100k</td>\n",
       "      <td>5486.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>1</td>\n",
       "      <td>&lt;= 1,500</td>\n",
       "      <td>1 or 2</td>\n",
       "      <td>1 or 1.5</td>\n",
       "      <td>1 or less</td>\n",
       "      <td>0</td>\n",
       "      <td>3 or 4 occupants</td>\n",
       "      <td>&lt; $50k</td>\n",
       "      <td>3682.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Year built range Assessed value range  Number of stories  \\\n",
       "0            <1945        $100k - $150k                  1   \n",
       "1            <1945              < $100k                  1   \n",
       "2            <1945              < $100k                  1   \n",
       "3            <1945              < $100k                  1   \n",
       "4            <1945              < $100k                  1   \n",
       "\n",
       "  Square footage range Number of bedrooms Total number of bathrooms  \\\n",
       "0             <= 1,500             1 or 2                  1 or 1.5   \n",
       "1             <= 1,500             1 or 2                  1 or 1.5   \n",
       "2             <= 1,500             1 or 2                  1 or 1.5   \n",
       "3             <= 1,500             1 or 2                  1 or 1.5   \n",
       "4             <= 1,500             1 or 2                  1 or 1.5   \n",
       "\n",
       "  Number of kitchens Number of fireplaces Number of occupants  \\\n",
       "0          1 or less                    0    3 or 4 occupants   \n",
       "1          1 or less                    0    3 or 4 occupants   \n",
       "2          1 or less                    0    3 or 4 occupants   \n",
       "3          1 or less                    0    3 or 4 occupants   \n",
       "4          1 or less                    0    3 or 4 occupants   \n",
       "\n",
       "  Median income range  Average annual electric use (kWh)  \n",
       "0        $50k - $100k                             4309.0  \n",
       "1        $50k - $100k                             3218.5  \n",
       "2        $50k - $100k                             6938.0  \n",
       "3        $50k - $100k                             5486.0  \n",
       "4              < $50k                             3682.0  "
      ]
     },
     "execution_count": 356,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('Monroe_County_Single_Family_Residential__Building_Assets_and_Energy_Consumption__2017-2019.csv')\n",
    "data.drop(columns = ['Ethnic group','NYSERDA Energy Efficiency Program Participation','Average annual electric use (MMBtu)','Average annual gas use (MMBtu)','Average annual total energy use (MMBtu)'],inplace = True)\n",
    "print(data.shape)\n",
    "data.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9270a2b5",
   "metadata": {},
   "source": [
    "### 探索性分析\n",
    "\n",
    "查看缺失值情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 357,
   "id": "d2873cff",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year built range</th>\n",
       "      <th>Assessed value range</th>\n",
       "      <th>Number of stories</th>\n",
       "      <th>Square footage range</th>\n",
       "      <th>Number of bedrooms</th>\n",
       "      <th>Total number of bathrooms</th>\n",
       "      <th>Number of kitchens</th>\n",
       "      <th>Number of fireplaces</th>\n",
       "      <th>Number of occupants</th>\n",
       "      <th>Median income range</th>\n",
       "      <th>Average annual electric use (kWh)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>55143</td>\n",
       "      <td>55143</td>\n",
       "      <td>55143.000000</td>\n",
       "      <td>55143</td>\n",
       "      <td>55143</td>\n",
       "      <td>55143</td>\n",
       "      <td>55143</td>\n",
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       "      <td>55143</td>\n",
       "      <td>55143</td>\n",
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       "    <tr>\n",
       "      <th>unique</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>top</th>\n",
       "      <td>1945-1975</td>\n",
       "      <td>$100k - $150k</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1500 - 2500</td>\n",
       "      <td>3</td>\n",
       "      <td>1 or 1.5</td>\n",
       "      <td>1 or less</td>\n",
       "      <td>1 or more</td>\n",
       "      <td>Less than 3</td>\n",
       "      <td>&lt; $50k</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>freq</th>\n",
       "      <td>21088</td>\n",
       "      <td>20464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28139</td>\n",
       "      <td>32091</td>\n",
       "      <td>31081</td>\n",
       "      <td>55013</td>\n",
       "      <td>28013</td>\n",
       "      <td>28743</td>\n",
       "      <td>20836</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.792902</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9036.451191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.608729</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4862.853362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5757.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8143.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11213.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>174374.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Year built range Assessed value range  Number of stories  \\\n",
       "count             55143                55143       55143.000000   \n",
       "unique                4                    5                NaN   \n",
       "top           1945-1975        $100k - $150k                NaN   \n",
       "freq              21088                20464                NaN   \n",
       "mean                NaN                  NaN           1.792902   \n",
       "std                 NaN                  NaN           0.608729   \n",
       "min                 NaN                  NaN           1.000000   \n",
       "25%                 NaN                  NaN           1.000000   \n",
       "50%                 NaN                  NaN           2.000000   \n",
       "75%                 NaN                  NaN           2.000000   \n",
       "max                 NaN                  NaN           3.000000   \n",
       "\n",
       "       Square footage range Number of bedrooms Total number of bathrooms  \\\n",
       "count                 55143              55143                     55143   \n",
       "unique                    3                  3                         3   \n",
       "top             1500 - 2500                  3                  1 or 1.5   \n",
       "freq                  28139              32091                     31081   \n",
       "mean                    NaN                NaN                       NaN   \n",
       "std                     NaN                NaN                       NaN   \n",
       "min                     NaN                NaN                       NaN   \n",
       "25%                     NaN                NaN                       NaN   \n",
       "50%                     NaN                NaN                       NaN   \n",
       "75%                     NaN                NaN                       NaN   \n",
       "max                     NaN                NaN                       NaN   \n",
       "\n",
       "       Number of kitchens Number of fireplaces Number of occupants  \\\n",
       "count               55143                55143               55143   \n",
       "unique                  2                    2                   3   \n",
       "top             1 or less            1 or more         Less than 3   \n",
       "freq                55013                28013               28743   \n",
       "mean                  NaN                  NaN                 NaN   \n",
       "std                   NaN                  NaN                 NaN   \n",
       "min                   NaN                  NaN                 NaN   \n",
       "25%                   NaN                  NaN                 NaN   \n",
       "50%                   NaN                  NaN                 NaN   \n",
       "75%                   NaN                  NaN                 NaN   \n",
       "max                   NaN                  NaN                 NaN   \n",
       "\n",
       "       Median income range  Average annual electric use (kWh)  \n",
       "count                55143                       55143.000000  \n",
       "unique                   4                                NaN  \n",
       "top                 < $50k                                NaN  \n",
       "freq                 20836                                NaN  \n",
       "mean                   NaN                        9036.451191  \n",
       "std                    NaN                        4862.853362  \n",
       "min                    NaN                           0.000000  \n",
       "25%                    NaN                        5757.750000  \n",
       "50%                    NaN                        8143.500000  \n",
       "75%                    NaN                       11213.250000  \n",
       "max                    NaN                      174374.000000  "
      ]
     },
     "execution_count": 357,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe(include = 'all')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab075e50",
   "metadata": {},
   "source": [
    "年均用电量趋势图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 358,
   "id": "6b8650fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 648x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize = (9,5))\n",
    "\n",
    "sns.distplot(data[\"Average annual electric use (kWh)\"])\n",
    "plt.xlim(0,40000)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23f11a63",
   "metadata": {},
   "source": [
    "收入,住户个数与年均用电量热力图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 359,
   "id": "f36b2118",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 648x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = data.pivot_table(index='Median income range', columns='Number of occupants',values = 'Average annual electric use (kWh)',aggfunc='mean')\n",
    "plt.figure(figsize = (9,5))\n",
    "sns.heatmap(dataset)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cef3a7a2",
   "metadata": {},
   "source": [
    "浴室个数,厨房个数,壁炉个数对年均用电量的影响"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 360,
   "id": "dc28a0d9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 6))\n",
    "ax1 = plt.subplot(1, 3, 1)\n",
    "plt.title(\"bathrooms\")\n",
    "sns.barplot(x=\"Total number of bathrooms\",y =\"Average annual electric use (kWh)\",hue=\"Total number of bathrooms\",data=data, log=True)\n",
    "ax2 = plt.subplot(1, 3, 2)\n",
    "plt.title(\"kitchens\")\n",
    "sns.barplot(x=\"Number of kitchens\",y =\"Average annual electric use (kWh)\",hue=\"Number of kitchens\",data=data, log=True)\n",
    "ax3 = plt.subplot(1, 3, 3)\n",
    "plt.title(\"fireplaces\")\n",
    "sns.barplot(x=\"Number of fireplaces\",y =\"Average annual electric use (kWh)\",hue=\"Number of fireplaces\",data=data, log=True)\n",
    "plt.subplots_adjust(wspace=0.5, hspace=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61e009b6",
   "metadata": {},
   "source": [
    "### 数据预处理"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0de6594b",
   "metadata": {},
   "source": [
    "#### 类型变量处理\n",
    "得到类别变量和数值变量的变量名。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 361,
   "id": "1265789d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(['Square footage range',\n",
       "  'Number of bedrooms',\n",
       "  'Total number of bathrooms',\n",
       "  'Number of kitchens',\n",
       "  'Number of fireplaces',\n",
       "  'Number of occupants',\n",
       "  'Median income range'],\n",
       " ['Number of stories',\n",
       "  'Average annual electric use (kWh)',\n",
       "  'Assessed value range',\n",
       "  'Year built range'])"
      ]
     },
     "execution_count": 361,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_cols = ['Square footage range','Number of bedrooms','Total number of bathrooms','Number of kitchens',\n",
    "                    'Number of fireplaces','Number of occupants','Median income range']\n",
    "numeric_cols = list(set(data.columns) - set(categorical_cols))\n",
    "categorical_cols,numeric_cols"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49932a04",
   "metadata": {},
   "source": [
    "将数据集中的类型变量做独热编码。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 362,
   "id": "8910445c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Square footage range_&lt;= 1,500</th>\n",
       "      <th>Square footage range_&gt;=2500</th>\n",
       "      <th>Number of bedrooms_3</th>\n",
       "      <th>Number of bedrooms_4 or more</th>\n",
       "      <th>Total number of bathrooms_2 or 2.5</th>\n",
       "      <th>Total number of bathrooms_3 or more</th>\n",
       "      <th>Number of kitchens_2 or more</th>\n",
       "      <th>Number of fireplaces_1 or more</th>\n",
       "      <th>Number of occupants_Less than 3</th>\n",
       "      <th>Number of occupants_More than 4</th>\n",
       "      <th>Median income range_$50k - $100k</th>\n",
       "      <th>Median income range_&lt; $50k</th>\n",
       "      <th>Median income range_&gt; $150k</th>\n",
       "      <th>Number of stories</th>\n",
       "      <th>Average annual electric use (kWh)</th>\n",
       "      <th>Assessed value range</th>\n",
       "      <th>Year built range</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>4309.0</td>\n",
       "      <td>$100k - $150k</td>\n",
       "      <td>&lt;1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3218.5</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>6938.0</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5486.0</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3682.0</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Square footage range_<= 1,500 Square footage range_>=2500  \\\n",
       "0                           1.0                         0.0   \n",
       "1                           1.0                         0.0   \n",
       "2                           1.0                         0.0   \n",
       "3                           1.0                         0.0   \n",
       "4                           1.0                         0.0   \n",
       "\n",
       "  Number of bedrooms_3 Number of bedrooms_4 or more  \\\n",
       "0                  0.0                          0.0   \n",
       "1                  0.0                          0.0   \n",
       "2                  0.0                          0.0   \n",
       "3                  0.0                          0.0   \n",
       "4                  0.0                          0.0   \n",
       "\n",
       "  Total number of bathrooms_2 or 2.5 Total number of bathrooms_3 or more  \\\n",
       "0                                0.0                                 0.0   \n",
       "1                                0.0                                 0.0   \n",
       "2                                0.0                                 0.0   \n",
       "3                                0.0                                 0.0   \n",
       "4                                0.0                                 0.0   \n",
       "\n",
       "  Number of kitchens_2 or more Number of fireplaces_1 or more  \\\n",
       "0                          0.0                            0.0   \n",
       "1                          0.0                            0.0   \n",
       "2                          0.0                            0.0   \n",
       "3                          0.0                            0.0   \n",
       "4                          0.0                            0.0   \n",
       "\n",
       "  Number of occupants_Less than 3 Number of occupants_More than 4  \\\n",
       "0                             0.0                             0.0   \n",
       "1                             0.0                             0.0   \n",
       "2                             0.0                             0.0   \n",
       "3                             0.0                             0.0   \n",
       "4                             0.0                             0.0   \n",
       "\n",
       "  Median income range_$50k - $100k Median income range_< $50k  \\\n",
       "0                              1.0                        0.0   \n",
       "1                              1.0                        0.0   \n",
       "2                              1.0                        0.0   \n",
       "3                              1.0                        0.0   \n",
       "4                              0.0                        1.0   \n",
       "\n",
       "  Median income range_> $150k Number of stories  \\\n",
       "0                         0.0                 1   \n",
       "1                         0.0                 1   \n",
       "2                         0.0                 1   \n",
       "3                         0.0                 1   \n",
       "4                         0.0                 1   \n",
       "\n",
       "  Average annual electric use (kWh) Assessed value range Year built range  \n",
       "0                            4309.0        $100k - $150k            <1945  \n",
       "1                            3218.5              < $100k            <1945  \n",
       "2                            6938.0              < $100k            <1945  \n",
       "3                            5486.0              < $100k            <1945  \n",
       "4                            3682.0              < $100k            <1945  "
      ]
     },
     "execution_count": 362,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ohe = OneHotEncoder(drop = 'first', sparse = False)\n",
    "data = np.hstack((ohe.fit_transform(data[categorical_cols]), data[numeric_cols]))\n",
    "cols = sum([(categorical_cols[i] + '_'+ ohe.categories_[i][1:]).tolist() for i in range(len(categorical_cols))],[])+ numeric_cols\n",
    "data = pd.DataFrame(data, columns = cols)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30e9fbce",
   "metadata": {},
   "source": [
    "在做完独热编码后，列索引对应的自变量意义如下：\n",
    "\n",
    "* 列索引0 - 1：变量`Square footage range`是否为`<= 1,500`、`>=2500`，1为是，0为否；\n",
    "* 列索引2 - 3：变量`Number of bedrooms`是否为`3`、`4 or more`，1为是，0为否；\n",
    "* 列索引4 - 5：变量`Total number of bathrooms`是否为`2 or 2.5`、`3 or more`，1为是，0为否；\n",
    "* 列索引6：变量`Number of kitchens`是否为`1 or more`，1为是，0为否；\n",
    "* 列索引7：变量`Number of fireplaces`是否为`1 or more`，1为是，0为否；\n",
    "* 列索引8 - 9：变量`Number of occupants`是否为`Less than 3`和`More than 4`，1为是，0为否；\n",
    "* 列索引10 - 12：变量`Median income range`是否为`50k− 100k`和`< 50k`、`> 150k`，1为是，0为否；\n",
    "* 列索引13 - 16：变量`Year built range`、`Average annual electric use (kWh)`、`Assessed value range`、`Number of stories`、"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 363,
   "id": "57f25dcd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Square footage range_&lt;= 1,500</th>\n",
       "      <th>Square footage range_&gt;=2500</th>\n",
       "      <th>Number of bedrooms_3</th>\n",
       "      <th>Number of bedrooms_4 or more</th>\n",
       "      <th>Total number of bathrooms_2 or 2.5</th>\n",
       "      <th>Total number of bathrooms_3 or more</th>\n",
       "      <th>Number of kitchens_2 or more</th>\n",
       "      <th>Number of fireplaces_1 or more</th>\n",
       "      <th>Number of occupants_Less than 3</th>\n",
       "      <th>Number of occupants_More than 4</th>\n",
       "      <th>Median income range_$50k - $100k</th>\n",
       "      <th>Median income range_&lt; $50k</th>\n",
       "      <th>Median income range_&gt; $150k</th>\n",
       "      <th>Number of stories</th>\n",
       "      <th>Average annual electric use (kWh)</th>\n",
       "      <th>Assessed value range</th>\n",
       "      <th>Year built range</th>\n",
       "      <th>id</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1.0</td>\n",
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       "      <td>4309.0</td>\n",
       "      <td>$100k - $150k</td>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3218.5</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>6938.0</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5486.0</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3682.0</td>\n",
       "      <td>&lt; $100k</td>\n",
       "      <td>&lt;1945</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Square footage range_<= 1,500 Square footage range_>=2500  \\\n",
       "0                           1.0                         0.0   \n",
       "1                           1.0                         0.0   \n",
       "2                           1.0                         0.0   \n",
       "3                           1.0                         0.0   \n",
       "4                           1.0                         0.0   \n",
       "\n",
       "  Number of bedrooms_3 Number of bedrooms_4 or more  \\\n",
       "0                  0.0                          0.0   \n",
       "1                  0.0                          0.0   \n",
       "2                  0.0                          0.0   \n",
       "3                  0.0                          0.0   \n",
       "4                  0.0                          0.0   \n",
       "\n",
       "  Total number of bathrooms_2 or 2.5 Total number of bathrooms_3 or more  \\\n",
       "0                                0.0                                 0.0   \n",
       "1                                0.0                                 0.0   \n",
       "2                                0.0                                 0.0   \n",
       "3                                0.0                                 0.0   \n",
       "4                                0.0                                 0.0   \n",
       "\n",
       "  Number of kitchens_2 or more Number of fireplaces_1 or more  \\\n",
       "0                          0.0                            0.0   \n",
       "1                          0.0                            0.0   \n",
       "2                          0.0                            0.0   \n",
       "3                          0.0                            0.0   \n",
       "4                          0.0                            0.0   \n",
       "\n",
       "  Number of occupants_Less than 3 Number of occupants_More than 4  \\\n",
       "0                             0.0                             0.0   \n",
       "1                             0.0                             0.0   \n",
       "2                             0.0                             0.0   \n",
       "3                             0.0                             0.0   \n",
       "4                             0.0                             0.0   \n",
       "\n",
       "  Median income range_$50k - $100k Median income range_< $50k  \\\n",
       "0                              1.0                        0.0   \n",
       "1                              1.0                        0.0   \n",
       "2                              1.0                        0.0   \n",
       "3                              1.0                        0.0   \n",
       "4                              0.0                        1.0   \n",
       "\n",
       "  Median income range_> $150k Number of stories  \\\n",
       "0                         0.0                 1   \n",
       "1                         0.0                 1   \n",
       "2                         0.0                 1   \n",
       "3                         0.0                 1   \n",
       "4                         0.0                 1   \n",
       "\n",
       "  Average annual electric use (kWh) Assessed value range Year built range  id  \n",
       "0                            4309.0        $100k - $150k            <1945   0  \n",
       "1                            3218.5              < $100k            <1945   1  \n",
       "2                            6938.0              < $100k            <1945   2  \n",
       "3                            5486.0              < $100k            <1945   3  \n",
       "4                            3682.0              < $100k            <1945   4  "
      ]
     },
     "execution_count": 363,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "id=list(data.index)\n",
    "data['id']=id\n",
    "data.to_csv('data_power_consumption.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "651f47d1",
   "metadata": {},
   "source": [
    "导入分析模块"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 364,
   "id": "fa20e49f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95d9d219",
   "metadata": {},
   "source": [
    "构建可视化类对数据进行分析"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 365,
   "id": "d4e6d30f",
   "metadata": {},
   "outputs": [],
   "source": [
    "class EnergyFingerPrints():\n",
    "\n",
    "    def __init__(self, data):\n",
    "        # 统计每个聚类簇的中心点\n",
    "        self.means = []\n",
    "        self.data = data\n",
    "\n",
    "    def elbow_method(self, n_clusters):\n",
    "        fig, ax = plt.subplots(figsize=(8, 4))\n",
    "        distortions = []\n",
    "\n",
    "        for i in range(1, n_clusters):\n",
    "            km = KMeans(n_clusters=i,\n",
    "                        init='k-means++',  # 初始中心簇的获取方式，k-means++一种比较快的收敛的方法\n",
    "                        n_init=10,  # 初始中心簇的迭代次数\n",
    "                        max_iter=300,  # 数据分类的迭代次数\n",
    "                        random_state=0)  # 初始化中心簇的方式\n",
    "            km.fit(self.data)\n",
    "            distortions.append(km.inertia_)  # inertia计算样本点到最近的中心点的距离之和\n",
    "\n",
    "        plt.plot(range(1, n_clusters), distortions, marker='o', lw=1)\n",
    "        plt.xlabel('聚类数量')\n",
    "        plt.ylabel('至中心点距离之和')\n",
    "        plt.show()\n",
    "\n",
    "    def get_cluster_counts(self):  # 统计聚类簇和每个簇中样本的数量\n",
    "        return pd.Series(self.predictions).value_counts()\n",
    "\n",
    "    def get_cluster(self):\n",
    "        return pd.DataFrame(self.predictions)\n",
    "\n",
    "    def labels(self, n_clusters):  # 确定每簇中样本的具体划分\n",
    "        self.n_clusters = n_clusters\n",
    "        return KMeans(self.n_clusters, init='k-means++', n_init=10, max_iter=300, random_state=0).fit(self.data).labels_\n",
    "\n",
    "    def fit(self, n_clusters):  # 基于划分簇的数量，对数据进行聚类分析\n",
    "        self.n_clusters = n_clusters\n",
    "        self.kmeans = KMeans(self.n_clusters)\n",
    "        self.predictions = self.kmeans.fit_predict(self.data)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94643b81",
   "metadata": {},
   "source": [
    "分析各簇中心点与样本的距离（第一种分类标准：根据房子大小、收入、居住人数）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 366,
   "id": "51d240b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = pd.read_csv('data_power_consumption.csv')\n",
    "data = dataset[['Square footage range_<= 1,500','Square footage range_>=2500','Median income range_$50k - $100k','Median income range_< $50k','Median income range_> $150k','Average annual electric use (kWh)','Number of occupants_Less than 3','Number of occupants_More than 4']]\n",
    "data = np.array(data)\n",
    "energy_clusters = EnergyFingerPrints(data)\n",
    "energy_clusters.elbow_method(n_clusters=13)\n",
    "energy_clusters.fit(n_clusters=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbe3a17b",
   "metadata": {},
   "source": [
    "统计各个簇的数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 367,
   "id": "58fa8b55",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1    23183\n",
       "0    21575\n",
       "2     9146\n",
       "3     1239\n",
       "dtype: int64"
      ]
     },
     "execution_count": 367,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count = energy_clusters.get_cluster_counts()\n",
    "count"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "125673da",
   "metadata": {},
   "source": [
    "每个id所属的簇"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "id": "2eeabf16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>28059</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28058</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28057</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28056</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55138</th>\n",
       "      <td>32851</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55139</th>\n",
       "      <td>32849</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55140</th>\n",
       "      <td>32848</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55141</th>\n",
       "      <td>7931</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55142</th>\n",
       "      <td>55142</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>55143 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id  cluster\n",
       "0          0        0\n",
       "1      28059        0\n",
       "2      28058        0\n",
       "3      28057        0\n",
       "4      28056        0\n",
       "...      ...      ...\n",
       "55138  32851        3\n",
       "55139  32849        3\n",
       "55140  32848        3\n",
       "55141   7931        3\n",
       "55142  55142        3\n",
       "\n",
       "[55143 rows x 2 columns]"
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group=energy_clusters.labels(n_clusters = 4)\n",
    "data2=pd.read_csv('data_power_consumption.csv')\n",
    "num=data2['id']\n",
    "cls=pd.DataFrame(list(num))\n",
    "cls['cluster']=list(group)\n",
    "cls.columns=['id','cluster']\n",
    "cls=cls.sort_values(by='cluster',ascending=True) \n",
    "cls.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 369,
   "id": "d410df4c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([    0, 28059, 28058, ...,  4411,   166,  4786], dtype=int64)"
      ]
     },
     "execution_count": 369,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第一类\n",
    "np.array(cls.loc[cls.cluster ==0].id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 370,
   "id": "56a85c01",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([47605, 42273, 40484, ..., 49201, 49296, 25005], dtype=int64)"
      ]
     },
     "execution_count": 370,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第二类\n",
    "np.array(cls.loc[cls.cluster ==1].id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 371,
   "id": "46c0d7bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 4917, 53877, 15102, ..., 35793,  1629, 32654], dtype=int64)"
      ]
     },
     "execution_count": 371,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第三类\n",
    "np.array(cls.loc[cls.cluster ==2].id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 372,
   "id": "3e652586",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([47971,  3576, 43258, ..., 32848,  7931, 55142], dtype=int64)"
      ]
     },
     "execution_count": 372,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第四类\n",
    "np.array(cls.loc[cls.cluster ==3].id)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91a34c06",
   "metadata": {},
   "source": [
    "聚类后的散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 373,
   "id": "1ab89841",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cls = energy_clusters.get_cluster()\n",
    "cls_data = pd.DataFrame(data)\n",
    "cls_data = pd.merge(cls_data, cls, left_index=True, right_index=True)\n",
    "cls_data=cls_data.reset_index()\n",
    "color = [\"red\",\"pink\",\"orange\",\"gray\"]\n",
    "plt.figure(figsize=(15,10))\n",
    "for i in range(4):\n",
    "    plt.scatter(cls_data.loc[cls_data['0_y']==i,'index'], cls_data.loc[cls_data['0_y']==i,5] #就是取出y_pred是0，1，2，3的那一簇的X\n",
    "                ,marker='o' #点的形状\n",
    "                ,s=8 #点的大小\n",
    "                ,c=color[i]\n",
    "                )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d480d8e",
   "metadata": {},
   "source": [
    "每个用户的用电曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 374,
   "id": "4c105fb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.lineplot(x=cls_data.index, y=5, hue='0_y', data=cls_data)\n",
    "plt.ylabel('年均用电量')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2dd92e49",
   "metadata": {},
   "source": [
    "分析各簇中心点与样本的距离（分类标准：浴室数量、厨房数量、壁炉数量）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "id": "8e250216",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lnPnLN9LWpt9BIiJyYOLpnX4VweAu7u4rzexEd19iZkcCSxNb3sA1oTSfwrxMXv2wjuPHFkVdjoiIpKB4zsRvBU4C5ppZFnB++FwBaOixg9B+Ni4iInIg4gnxOne/F9hE0Bs9Fj6fDHw+gbUNeO3Xxd3VpC4iIr0XT4i3mtn3gSzgVwRN8JnhY4aZqYf6ATpy5FAc560NO6IuRUREUlCP18TdvX1Al5vD5++2bzOz/w7fo6XvSxv4zIzzKkcy/82NTBk1LOpyREQkxRzsLWZvAxP7opDBqmpKOfN0XVxERA5Aj2fiZlYJNAFHAaM7bHoLqCZoYpcDNPWQQup2t7C6tp6JpflRlyMiIikknjPxbILr4d8A5gKPEkyK8py7X+vuKxJX3sCXlmZUqZe6iIgcgHjnEw9euK919w8IzswrzOxaM/vbhFU3SFRXljNfo7eJiEgvxTPYSxZBkHcV+P/u7k19W9LgM338cNZ+tJuaugYqCnOjLkdERFJEPGfiVcAFwJgO69zd1wCFZja5pzcws8vNbJmZLTGzizptyzWze81sqZm9aGaDLsUy09M464gynY2LiEiv9Bji7v49d/8e8EGH1WZmVcD59DAJipkNBa4GZgDnALeYWXaHXb4PLHL3ae5+krs39PaPGAjOq1QvdRER6Z1e3WJmZmPMbCyQA2wDfufuK3s4rAp4zN2b3H0HsAiYHr5fFvBJd5/T+9IHlk8cWsLbG3ZQu1NXJ0REJD69CfGfA58GPgXcB9QAt5rZaT0cNxpY22G5ho/nIx8LbAyb058zs5v3ORows5lhc/vS2traXpScOnIy0/nkpFKefntT1KWIiEiKiKdjGwDuPreL1d8ys1E9HJpFMN56u7bwAVACHE3Q1L4J+L2ZVbv7vE6fPQeYAzBt2rQBO9B4dWU5Dy1dx99PH9PzziIiMugd0IhtZjbWzEoA3H19D7tvBDoGfQWwLnxdC7zi7uvdPQY8RjCozKBU39jKwpW1jL/+T3zih39m7qs1UZckIiJJrLfXxC8wszsJBnuJd+KTp4CLzSzTzIYBU4GXw22rgTIzGx4unwa82puaBoq5r9bwvcffwgl6CtbUNXDDw28oyEVEpFtxh7iZfQZoBf6RYB7x48yssKfjwjP1u4HngacJJlI5x8wu8mAOzm8Dj5nZQmCjuz/d679iALh9/goaWmJ7rWtoiXH7fA2IJyIiXYvrmriZzQD+6O5NZpYOLCNoFp8PnNjT8e4+G5jdzbZFwClxVzxAra/r+s667taLiIj0eCZuZjcAx7WPzObuMXf/q7s/Aew2s7g7x0n3RnUzUlt360VERPYb4mY2C1js7nd2s0uGu7f2eVWD0HVVk8nNTN9rnQFHVQwluOogIiKyt57Oon/k7g1mdj7wyXBdxw5tjyemrMHnwqkVQHBtfH1dA6MKc/naJyfwX0vW8sMn3uH68w7HLN6+hCIiMhhYvGd5ZnYm0EJwZh7raf9EmTZtmi9dujSqj+93dbub+cLdL3HsIYXM+vQU0tIU5CIig42ZLXP3aZ3X9+YWs78Cw4F/MbPbzey4PqtOulWYl8V9XzmRtzfs4Nt/+CuxNjWti4hIIO4Qd/ct7v6ou18P/BPQnLiypKOhOZnc+6XpbNzeyNW/f5WWWFvPB4mIyIB3QCO2hZOZvNnXxUj38rIyuOuKaTQ0x/j6/a/Q1BrZFQ0REUkScYW4md1pZj8IH7eFo7ZJP8vJTOeXnz+erPQ0vnLvUhqaFeQiIoNZvGfiR7r7jeHjBuDIRBYl3cvKSOPnlx5LaUE2V9zzEvVNusNPRGSwOqDmdIlWRnoad1x8DIeNyOfyu5awfXdL1CWJiEgE4hmxrQoYbmbnho+9lhNfonQlLc249cJKThhbxKW/epEt9U1RlyQiIv0snjPxRoKJtRqBpi6WJSJmxk3nH8E5R4zgktkvsGlHY9QliYhIP+px3HN3/4uZbXP3he3rOi9LdMyMb547mZysdD43+wXu/8qJjC7Ki7osERHpB/FeE+88TJiGDUsyXz/9UK6cMY5LZr/Ie1t2RV2OiIj0g3hnIHvDzH7Ax+H9RoLqkYPwxU+MJzcrnUvnvMBvv3wik8oKoi5JREQSqMcQN7OR7v6P3Ww7192f7Puy5EBdcsIYcjLTufyuJdzzxROorBgWdUkiIpIg8TSn3w9gZsPM7Mbw9VfCbdcnqjA5cH97bAW3/G0lX7znJZZ9sC3qckREJEHiHbEtHXgIeDlcdVn7pkQUJQevurKcOz57DDN/s5QXVm+NuhwREUmAeELcCOYSvwsYkdhypC+dPnkEd152HN/4r1dYsGJz1OWIiEgfi+tM3N3/DCwEzgznFS8KnwsTWJv0gZMnFjPnC9O49qHXmffmxqjLERGRPhRPiE82s68DW4CxfNyErqb0FHH82CJ+feV0vvvomzz6Wk3U5YiISB+JJ8RXAH8GvgRscvdngG3hc10Ca5M+VFkxjPu/ciK3/c87PPDy2qjLERGRPhBPiLu7vwM8DRSF69rPwj2eDzGzy81smZktMbOLuthuZvaMpjhNrEllBfxu5kn82zOruGfRe1GXIyIiBynejm24+xqCs3GAX3fctt+DzYYCVwMzgHOAW8wsu9NuXwU+jKMWOUjjS4bwwNdO4teL3+c/FqyKuhwRETkI8YT45e0v3H1j+HxvuOr7cRxfBTzm7k3uvgNYBExv32hmI4HzgXu7OV762OiiPB782sk8/EoNP3lyBe5xNaiIiEiS6THE3X39frY9G8dnjAY6XoStAco7LN8BfIf9NM2b2UwzW2pmS2tra+P4SOlJ2dAcHph5Ek+/vZlb//S2glxEJAXFOwHKwcgCYh2W28IHZnYhsCK85t4td5/j7tPcfVppaWnCCh1sivOz+f1XT2LpB9v4p7lv0tamIBcRSSX9EeIbgVEdliuAdeHrzwOnmdk84MfAp83sa/1Qk4SG5WVy35en8+7meq7979dpjbVFXZKIiMSpP0L8KeBiM8s0s2HAVMLhW939Ync/292rgW8Dj7v77H6oSTooyMnk3iunU7uziat//xrNrQpyEZFUkPAQD6+p3w08T3Cb2s3AOV3daibRyc1K564rptHU2sY/3LeMxpZYzweJiEikLNU6NE2bNs2XLl0adRkDVkusjWseeI263S3M+cLx5GXFO+W8iIgkipktc/dpndf3R3O6pJDM9DR+fulURg7L4Qv/+RI7GluiLklERLqh0yzZR3qa8aPPHM2sx5dz/s+fo7XN2bi9kVGFuVxXNZkLp1ZEXaKIiKAzcelGWpox9ZBCNmxvZMP2RhyoqWvghoffYO6rmkRFRCQZKMSlW3c8uZLWTveON7TEuH3+iogqEhGRjhTi0q31dQ1drq+pa2DD9q63iYhI/1GIS7dGFeZ2uX5IdjrVP3uObz74Gm9v2NHPVYmISDuFuHTruqrJ5Gam77UuNzOdf7nwKBZedwYTS/O54u6X+MLdL/H8u1s0/rqISD/TfeKyX3NfreH2+StYX9fQZe/0ptYYj762nl8tXENmehozT5vA+UePJDNdvw9FRPpKd/eJK8SlT7S1OX9ZWcvshatZu3U3XzplPJeccAgFOZlRlyYikvK6C3HdJy59Ii3NOOPwEZxx+Aj+uq6OOQvXcOezq7jkhEO4csZ4yoflRF2iiMiAozZP6XNHjy7kzsuO4/FvnEJTSxtVP1vItx58nRUbd0ZdmojIgKLmdEm4ut3N3L9kLb9e/D5HjhzKzNMmMGNiMWYWdWkiIilB18Qlck2tMea+WsOchWvIyUxn5mkT+Juj1AlORKQnCnFJGm1tzrMrNjNn4RrWbWvgyk+M49LpY8jPVhcNEZGuqGObJI20NOOsI8o464gyXv+wjjnPreEXz67ikhPGcOUnxlE2VJ3gRETioXZMidQxhxTyi8uO47FvnEJjS4xzf7qQax9SJzgRkXioOV2SyrZdzdy/5APufeEDpowaysxTJ3CyOsGJyCCna+KSUhpbwk5wz60hLyudr546gfOPGklGelqPo8iJiAw0CnFJSW1tzp/f2cyc59ZQs62BE8YVMW/5Rhpb2vbsk5uZzm1/d5SCXEQGrO5CXNfEJamlpRlnH1nGg187mTsvm8r8TgEOmuNcRAYvhbikjKljivYJ8HY1dQ1sqW/q54pERKKlW8wkpYwqzKWmrmGf9dkZaZxx+wIqinI5eWIxJ08o5sQJxQzL1QQsIjJw9UuIm9nlwDeBVuCH7v5Ih203AtVANvCcu1/bHzVJarquajI3PPwGDS2xPevar4l/6uiRvFGzncWrt/KbFz7gmgdeY+KIfE6eUMzJE4s5YdxwhmhAGREZQBLesc3MhgJPA6cSBPVi4Hh3bwq3f9rdHw9fPwbc6u4vdfd+6tgm8fZOb2qN8draOhav3soLa7byZs12jhg5lBkTg1A/bkwROZnpEfwFIiK9E1nvdDP7LDDZ3W8Nl2cD97n7c13sezvwpLs/1d37KcTlQDU0x1j6wUdBqK/eyspNOzlmdCEzJhYz49Bijh5dqHHcRSQpRTns6mhgbYflGqC8805mlgfMAG7uYttMYCbAmDFjElOlDHi5Wemcelgppx5WCsCOxhZefu8jXli9le/OXc7aj3Zz/NiiINQnlnDkqKGkp2mQGRFJXv0R4llArMNyW/jYw8zSgXuB77v7Pr2W3H0OMAeCM/HElSqDydCczD1juEMwWtyS97ayePVWrnnwNTbvaOTECcV7mt8njSggTaEuIkmkP0J8IzCqw3IFsKe53ILxNH8F/Mnd5/dDPSJdKhqSRXXlSKorRwKweUcjL6wJmt7vWfQ+u5paOWliGOoTihlfMmTPcLAaRU5EotAf18RHAY8ApwB5wHxghru3hdvvBN5w99nxvJ+uiUtU1m3bzQvh9fTFq7cCMGNiMVmZaTzySg1NrRpFTkQSI9JhV83sa8CXCAaXuQkwgkDfDTwEvNJh92+5+7Lu3kshLsnA3Xl/624Wr97CrX98i4YuBqEpG5rN4uvP0nV1ETloGjtdJEHGX/8nuvu/KCczjQkl+Uwqy+ewsgIOG5HPpLICDhmep3AXkbhF2TtdZEDrbhS5isJc5l9zGqs21/Pupp28u7me3720lpWb6tm6q4kJJfkcVhaE+qFhuI9RuItILyjERQ5Sd6PIXVc1mfzsDI49pJBjDync65j6plZWb65n5aadrNpcz+9fWsu7m+vZUt/E+PYz9xEfn72PLR6icBeRfSjERQ5Se+e13vROz8/O4JhDCjmmU7jvampldW09KzfV8+7mnTzw8oes3LST2p1NjC8ZwqSyAiaV5XPoiOB5zPA8MroZoEY95kUGPl0TF0kBu5tbw2b5elZu3smq8HnzjiDcDysrYNKIoHn+sLICXl+7jZvmLu9yjHkFuUjq0TVxkRSWl5XB0aMLOXp04V7rdze3snrzLlaG19wfWrqOdzfXs/aj3fu8R0NLjB/Ne0chLjKA6ExcZADaX4/5kvwsxpcMYXzJEMaVDGFCyRDGl+QztjhPE8KIJCmdiYsMIt33mM/hD1d9gve27Aof9fz3B3W8t6WeD7c1UJqfzbiSvDDk8xlfksf4knxGF+VqchiRJKQQFxmAuu8xfzjlw3IoH5bDyROL9zqmNdbG+rpG1myp5/0w5Bes2Mz7W3exaXsTFUW5wdl78RDGlw5hfPg8cmhO3GPKq7OdSN9SiIsMQAfSYz4jPY0xxXmMKc6DyXtva2yJ8eFHu/ecwS+v2c4fX1/Pe1t2saOxhbHDg+b5juE+rngIJflZe40v3/GHRU1dAzc8/MZe9YpI7+iauIgclPqm1j1n7u3Pa8LntjbfE+jPrtjMzsbWfY6vKMxl0fVnRlC5SOrQNXERSYj87AwqK4ZRWTFsn23bdjXz3tZdvFe7i8deX9/l8TV1Dfyv/1xCaUF28Mjf+7kkP5vCvMw9Z/Qi8jGFuIgkTNGQLIqGZHHcmCL+9amVXXa2Ky3I5kunjKd2ZxO1O5tYt62B1z6sC5brm9iys4mGlhgl+UGgtwd8SUFWGPQ5YdhnUVqQTX52Rq8CX9fpJZUpxEWkX3TX2e6mvzmCMyaP2O+xjS0xttQ3saW+eU/Y1+5sYnXtLl5c81EQ9vVNbN7RhOOdwr7D2X14Zj8ifJ6/fKOu00tKU4iLSL84kM527XIy0xldlMfoorwe993V1MqW+o+Dvv1sfvn67eFyM1vCbS2xtn3up29oifHdR99kS30TQ3MzGZqTydDcDIbmZDIsXM7PyUjoWPZqHZB4KcRFpN9cOLUi4WE0JDuDIdkZjC0est/93J0JN/xPl9t2NrayblsDOzbsYGdjKzsaWtix57mFXU2t5GVlMDQnY5+gL+hiXfty+7aCnIxu77tXL37pDYW4iAxKZrbfaWRnXTCl22Pb2pz65jDUG1rZ0diyV9DvbGxl445GVm5qCbeF+zQG23Y2tpKdkbZP0BfkZPD0W5v2uuQAQevALX98i4qiXPKy0snLygifg9f9McOdWgeSk0JcRAat/U0juz9paRYEb04mFPX+c92dXc2xPWf2OxrC8G9q4dHXuu7Fv3VXMz984h12NbXS0BJjd3OM3eHrjPQ0hoSBnpuVzpCs9PA5WO4q+PM67LPndXYGuZnBc15WOtkZaZhZUrYO6EdFQCEuIoPWwVynPxhmRn52BvnZGYwid69td8zvuhd/RWEuf7hqxj7r3Z3GljZ2N7cGwd4cY3dzKw3NMXZ1et0Q7rOlvpndza3huthexwb7BsutsTbysjLY3dxKW6fOAw0tMa5/+K88u2Iz2Rlp5GSmd/mc3WG5u306PsfTqpCMPyra6+rv/5YU4iIyqPXHdfre6G3rgJmRG55JF3e5x4FrjbWxuyXGMbOe7HJ7Y0sbZ0weQWNLjKbWNhpbYuEPihgf7WqhqTVY7vjc1Gm5saWNxnB9Y2uMdLO9wz0zjeyMdHIy0/ase3HNVhpb2vaqpb1DYk1dA9kZaWRlpJGVHj6HrzMz0sjuuK7TPtnp6WRlpJGZbmT0cq6AqH5YKMRFRJJIVK0DXclIT2Noetp++w70ZV3uTkvMPw71Dj8OmlrbaAqfF6yo7fL49v4GW1vbaI7FaG5tCx6x4LmptY2W2N7rOu7T1OG1QYeQT+/yh0FmupGVkU5WehqLVtXS0MUPi9vnr1CIi4gMJqneOnCgzIysDCMrIw1yut+vYj8/Kq4/7/CDrsPdibX5XkHf1Dn4O/0YePrtTV2+1/ou6uxLCnEREdmvZGodgMT/qDAzMsIm9bys+I7p7ofFqMLcLvbuO/0S4mZ2OfBNoBX4obs/0mHbWcCPwm2/cff/6I+aREQkfsnUOpBsPyqg/1orOkv4LGZmNhR4GjgVyAYWA8e7e5OZpQFLgGpgR7jtAnff0N37aRYzERFJRonsnR7lLGZVwGPu3gQ0mdkiYDrwHHA88Lq7bw2LfBg4G/htP9QlIiLSZ6JorehdH/oDMxpY22G5BiiPY9seZjbTzJaa2dLa2q57JYqIiAw2/RHiWUDHMQTbwkdP2/Zw9znuPs3dp5WWliasUBERkVTSHyG+ERjVYbkCWBfHNhEREdmP/gjxp4CLzSzTzIYBU4GXw20vAqea2VAzywQuAOb1Q00iIiIpL+Ed29x9vZndDTxP8KPhJuAcM8tz90fM7J8Igj4N+Dd3357omkRERAaChN9i1tfMrBb4IOo6EqwE2BJ1ESlA31N89D3FR99TfPQ99SwR39FYd9+nU1jKhfhgYGZLu7ofUPam7yk++p7io+8pPvqeetaf31F/XBMXERGRBFCIi4iIpCiFeHKaE3UBKULfU3z0PcVH31N89D31rN++I10TFxERSVE6ExcREUlRCnEREZEUpRAXEZH9MrMCMxsTdR3JLKrvSCGeRMws3cx+amYLzGyZmV0TdU3JysxyzOwtM7s26lqSmZmVmNmjZrbEzJ6Mup5kZGbfNLNFZvaymV0edT3JxMyKzOwRYBXwuQ7rf2JmL5nZc2Y2KboKo9fVd2RmI83sofDf8pfM7MxEfX5/zCcu8csAnnD3a8wsHXjJzH7n7hujLiwJfZePx+CX7v0H8Et3n2dmFnUxycbMDgEuBE4BsoG/AvdHWVOSaQVmEcx5UQJgZucAQ919upkdD/wM+JuoCkwC+3xHQCFwvbuvNrORwP+E2/uczsSTiLs3ufuT4esYsAYoiLaq5GNmRxPMO/9s1LUks/AfjwJ3nwfguhWlK80EUyKnAfnAR9GWk1zcfae7v95p9YXAveH2ZcAYMxu0WdLVd+Tub7v76vD1BhKYtYP2i092ZlYOlLr7u1HXkkzCfyx+CHwn6lpSQCWwwcz+EDZ7zoy6oGTj7psIziQXAI8B+o56NhpY22F5M1AcUS1Jz8yqCP77Sgg1pychM8sDfgtcHXUtSegfgQfcfYtah3tUAhwFnE1wxvmUmT3v7m9FW1byMLMC4CKC/66mAl8H/iHSopJfFhDrsNwWPqQTM5sM3Ah8KlGfoRBPMmaWDfwe+HEXzVgClwDbzezvgQog08xWufvcaMtKSrXAc+3T+5rZfGAKoBD/2OeBZ9z9VeBVM6sys0p3fzPqwpLYRmAUUBMuF6HLEPsws7HAXcBl7r4zUZ+jEE8iZpYB3AfMcfenoq4nGbn7ye2vzeyLQIkCvFsvArPMLIfgTPxk4MFoS0o6zcARENwdAhwC1EdaUfKbR/Dj5+WwY9sK9bfYW9gf5V7gCnf/MJGfpRBPLl8GPgmUdrh16nJ3r9nPMSJdcvd6M/sJ8GeC5s773X1FxGUlm98C95jZCwRNxPe5+/vRlpQ8zGw48DBBR9JMM/sUwb9TZ5jZYoIfQVdEWGLkuvmONhC0VtwdXvardffPJuTz9QNKREQkNal3uoiISIpSiIuIiKQohbiIiEiKUoiLiIikKIW4iIhIilKIi4iIpCiFuIiISIrSYC8iA5yZvU4w2Mt2YBxwD8F46jGgyd2rwv2uAF4DSgn+bVgPHOXu93d4r8vD9YcAw4BfAF9199mdPvOLwNeApi5KetHdr++zP1BkEFOIiwx83wJOA1YSjAg4BxgCzAWqzayCj+fQzgbyACMYfrTZzL4K/B1wLPDV8NghBLNXLQemmtkdwPHATM28J9J/FOIig8OnCc7Em9x9g5nNAt4hGNu5BjjdzCYSzHpWT/BvQzHwtru/Er7Hn81sW7h+DLCCIMjvB54HZnUI8DeAnxIMy9lZYwL+PpFBSSEuMoBZMHDzMILZlHYC55rZocDNwGXAl8xsOXApMBL4HnBKePgTwNVmdiVwQ/g+XwZmE0xzOgNoBf6dYI7pdeFnjgd+0kNd2939hb77S0UGJ42dLjKAmVkhwXzZHxCE7AVALsFZ9CHAH4EGoKh96lszOxlIc/dF4fJhBNfB2wAHLiaYyaqEoHPshQTTm37o7svCYy4AhhOc1Y8MP3NNWFahu9+VwD9bZNDQmbjIAObudWHHtlsI5nweQhCm6wk6mK01s2OBn4WzLQGMBz40s9YOb/UtglD+l/D56wQd4P4PUEBwPfzRDvuPIDhrbwKGApnA1nDbgj79I0UGMYW4yADn7q+Y2SqCIG5vKn8V+CXwBXd/DTgdwMzKgFnAYoLwvcfdd7e/l5mdDTwLVAAvuPtbZjYCmNRpTulXCEK7BZgcvtfL4TbN1y3SR9ScLjLAmdlVBE3fQ4CnCJrFzydoAh/h7j80szzgs8BxwE3hXOSHAVcBS9z9gfC9sgiugVcAvwGWANcQhPVv3P0NM5sert+f89x9Xh//qSKDjkJcZAAzs2LgOHd/yswmE5xxZwB/cfc3wzPrDcAlwOPu/nIX73Ee8D5Br/LLgUXu/qyZnUFwy9oPCO45vwH4g7u/nfi/TERAIS4iIpKyNOyqiIhIilKIi4iIpCiFuIiISIpSiIuIiKQohbiIiEiKUoiLiIikKIW4iIhIivr/koMeA0ripvMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = pd.read_csv('data_power_consumption.csv')\n",
    "data = dataset[['Number of bedrooms_3','Number of bedrooms_4 or more','Total number of bathrooms_2 or 2.5','Total number of bathrooms_3 or more','Number of kitchens_2 or more','Average annual electric use (kWh)','Number of fireplaces_1 or more']]\n",
    "data = np.array(data)\n",
    "energy_clusters = EnergyFingerPrints(data)\n",
    "energy_clusters.elbow_method(n_clusters=13)\n",
    "energy_clusters.fit(n_clusters=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e2b4070",
   "metadata": {},
   "source": [
    "统计各簇数量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "id": "452efbe2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    23183\n",
       "2    21575\n",
       "1     9146\n",
       "3     1239\n",
       "dtype: int64"
      ]
     },
     "execution_count": 376,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count = energy_clusters.get_cluster_counts()\n",
    "count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 377,
   "id": "f1b85888",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>cluster</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>28059</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>28058</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>28057</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28056</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55138</th>\n",
       "      <td>32851</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55139</th>\n",
       "      <td>32849</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55140</th>\n",
       "      <td>32848</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55141</th>\n",
       "      <td>7931</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55142</th>\n",
       "      <td>55142</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>55143 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          id  cluster\n",
       "0          0        0\n",
       "1      28059        0\n",
       "2      28058        0\n",
       "3      28057        0\n",
       "4      28056        0\n",
       "...      ...      ...\n",
       "55138  32851        3\n",
       "55139  32849        3\n",
       "55140  32848        3\n",
       "55141   7931        3\n",
       "55142  55142        3\n",
       "\n",
       "[55143 rows x 2 columns]"
      ]
     },
     "execution_count": 377,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "group=energy_clusters.labels(n_clusters = 4)\n",
    "data2=pd.read_csv('data_power_consumption.csv')\n",
    "num=data2['id']\n",
    "cls=pd.DataFrame(list(num))\n",
    "cls['cluster']=list(group)\n",
    "cls.columns=['id','cluster']\n",
    "cls=cls.sort_values(by='cluster',ascending=True) \n",
    "cls.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 378,
   "id": "5421c98d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([    0, 28059, 28058, ...,  4411,   166,  4786], dtype=int64)"
      ]
     },
     "execution_count": 378,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第一类\n",
    "np.array(cls.loc[cls.cluster ==0].id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "id": "ab455849",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([47605, 42273, 40484, ..., 49201, 49296, 25005], dtype=int64)"
      ]
     },
     "execution_count": 379,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第二类\n",
    "np.array(cls.loc[cls.cluster ==1].id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 380,
   "id": "b8d68ca9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 4917, 53877, 15102, ..., 35793,  1629, 32654], dtype=int64)"
      ]
     },
     "execution_count": 380,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第三类\n",
    "np.array(cls.loc[cls.cluster ==2].id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 381,
   "id": "c3a52aa6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([47971,  3576, 43258, ..., 32848,  7931, 55142], dtype=int64)"
      ]
     },
     "execution_count": 381,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 第四类\n",
    "np.array(cls.loc[cls.cluster ==3].id)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17b9ddb6",
   "metadata": {},
   "source": [
    "聚类后的散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 382,
   "id": "386e8511",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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I+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMUI+gAAAAAgxQj6AAAAACDFCPoAAAAAIMXqDvqMMcuMMWs7uTEAAAAAgPaqGfQZYwaNMX8laVzSNm/5HxhjnjbGjBpjbgqX9RtjvmiMecoY87fGmKFw+QpjzDeMMU8aY75mjFkSLl9rjPl+uPwLxphsuPwd4bInjTH3d2LHAQAAAGA+qKelb1rS70n6bbfAGPNBScuttbdK+qyk/xC+9WuSnrfWvkvSDkn/Olz+W5Ietta+W9KTkj4TLv99SZ8Ll1+U9Kvh8j+U9PFw+TuMMe9qYt8AAAAAYN6rGfRZa89Ya5+NLL5T0p+H7++WtNYYk/GXS/prST8T/vvnJX01/PeD4WtJ2mit/YG/PGwdLFhrD8V8HgAAAADQgGYncrlW0mHv9TFJOUmrJb0qSdbaaUkmfL/PWnsp/PdrklYZYwYl5b11vCrpaknXSHo5ZjkAAAAAoEHNBn0LJM14rwvhX5+11nrLp8P/Z92C8P3pKutIWl7GGPMbxpgxY8zY8ePHm9wNAAAAAEi3ZoO+1ySt8V4PSjopKW+MWSVJ4aQsLuiz3iQtV0l6XdIJSUPeOq6R9ErMut3yMtbaL1hrR6y1I6tWrWpyNwAAAAAg3ZoN+nZK+rgkGWM2SzoQtuAVlysY3/e98N8/lPSL4b8/Lunr1toZSa8aYzZFlk9IGjLGXBsuv1fS15vcTgAAAACY1/pqfcAYs1LSXyoYV9dvjPmIpH8s6QPGmB9KuiTpvvDj/0nSnxljPibplIKATZJ+V9IXjTG/LemQpE+Ey39T0p8aYwYkPWmt/U64/DOSvha2Dn7NWnugxf0EAAAAgHnJlA/Bm5tGRkbs2NhYtzcDAAAAALrCGLPbWjsS916z3TsBAAAAAHMAQR8AAAAApBhBHwAAAACkGEEfAAAAAKQYQR8AAAAApBhBHwCgI/L5vPbs2aN8Pt/tTQEAYF6r+Zw+AAAalc/ntWPHjuLr7du3K5fLdXGLAACYv2jpAwC03cTEhCTp8uXLZa8BAMDsI+gDALTd8PCwJKm/v7/sNQAAmH107wQAtF0ul9P27ds1MTGh4eFhunYCANBFBH0AgI7I5XIEewAA9AC6dwIAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABoST6f1549e5TP57u9KYjR1+0NAAAAADB35fN57dixo/h6+/btyuVyXdwiRNHSBwAAAKBpExMTkqTLly+XvUbvIOgDAAAA0LTh4WFJUn9/f9lr9A66dwIAAABoWi6X0/bt2zUxMaHh4WG6dvYggj4AAAAALcnlcgR7PYzunQAAAACQYgR9AAAAAJBiBH0AAAAAkGIEfQAAAACQYgR9AAAAAJBiBH0AAAAAkGIEfQAAAACQYgR9AAAAAJBiBH0AAAAAkGIEfQAAAACQYgR9AAAAAJBiBH0AAAAAkGIEfQAAAACQYgR9AAAAAJBiBH0AAAAAkGJNB33GmP/dGPOo93fGGHODMSbvLfsH4WdXGGO+YYx50hjzNWPMknD5WmPM98PlXzDGZMPl7wiXPWmMub89uwoAAAAA80/TQZ+19g+tte+31r5f0sck/UjSjKQn3XJr7RfDj/+WpIette+W9KSkz4TLf1/S58LlFyX9arj8DyV9PFz+DmPMu5rdTgAAAACYz9rVvfM+SV+s8v7PS/pq+O8Hw9eStNFa+wN/uTFmSFLBWnso5vMAAAAAgAa0K+j7VUlfkzQt6XpjzA+NMQ8YYwbD9/ustZfCf78maVX4Xt5bx6uSrpZ0jaSXY5YDAAAAABrUctBnjNkq6Rlr7Tlr7SvW2vXW2vdIelbSvws/lnWft9ZaBcHhAgXdQZ1C+Je0PPq7v2GMGTPGjB0/frzV3QAAAACAVGpHS9+vS/qvMcv/VNI7wn9bb5KWqyS9LumEpCHv89dIekVBS+CamOVlrLVfsNaOWGtHVq1a1fJOAAAAAEAatRT0GWNWSLrRWjsWvr7CGGPCtz8q6Znw3z+U9Ivhvz8u6evW2hlJrxpjNkWWT0gaMsZcGy6/V9LXW9lOAAAAAJiv+lr8/r2SHvJe3yrp3xtjTitozftUuPx3JX3RGPPbkg5J+kS4/Dcl/akxZkDBrJ/fCZd/RtLXwtbBr1lrD7S4nQAAAAAwL5lgiN3cNjIyYsfGxrq9GQAAAADQFcaY3dbakbj32jV7JwAAAACgBxH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAASK18Pq89e/Yon893e1O6pq/bGwAAAAAAnZDP57Vjx47i6+3btyuXy3Vxi7qDlj4AAAAAqTQxMSFJunz5ctnr+YagDwAAAEAqDQ8PS5L6+/vLXs83dO8EAAAAkEq5XE7bt2/XxMSEhoeH52XXTomgDwAAAECK5XK5eRvsOXTvBAAAAIAUI+gDAAAAgBQj6AMAAACAFCPoAwAAAIAUI+gDAAAAgBQj6AMAAACAFCPoAwAAADAv5fN57dmzR/l8vtub0lE8pw8AAADAvJPP57Vjx47i6+3bt6f2eX609AEAAACYdyYmJiRJly9fLnudRgR9AAAAAOad4eFhSVJ/f3/Z6zSieycAoCPy+bwmJiY0PDyc2u4yAIC5IS5PyuVy2r59+7zIqwj6AABtFzdOQtK8yFgBAL2lVp60adOmbm3arCHoAwC0nT9Oor+/X/v27dMTTzxRfD/Ng+UBAL2FPIkxfQCADoiOkzDGSJofg+UBAL2FPImWPgBAB0THSUjS6OjovBgsDwDoLeRJkrHWdnsbWjYyMmLHxsa6vRkAgCqY2AUA0CvSmCcZY3Zba0fi3qOlDwAwK3K5XGoyVgDA3Dbf8iTG9AEAAABAihH0AQAAAECKEfQBAAAAQIoR9AEAAABAihH0AQAAAECKEfQBAAAASK18Pq89e/Yon893e1O6hkc2AAAAAEilfD6vHTt2FF9v3759Xj2qwaGlDwAAAEAqTUxMSJIuX75c9nq+IegDAAAAkErDw8OSpP7+/rLX8w3dOwEAAACkUi6X0/bt2zUxMaHh4eF52bVTIugDAGDW5fP5eV8AAYDZksvl5n1aS9AHAMAsYlIBAMBsY0wfAACziEkFAKB3zJfHOdDSBwDALGJSAQDoDfOp5wVBHwAAs4hJBQCgN/g9L/r7+zUxMZHaNJmgDwCAWcakAgDQffOp5wVBHwAAAIB5Zz71vCDoAwAAADAvzZeeF8zeCQAAAAApRtAHAAAAAClG0AcAAAAglebLc/hqYUwfAAAAgNSZT8/hq6Wllj5jzCFjzKPh3x+Ey/7AGPO0MWbUGHNTuKzfGPNFY8xTxpi/NcYMhctXGGO+YYx50hjzNWPMknD5WmPM98PlXzDGZFvdUQAAAADzh/8cPv/1fNRq987z1tr3h3//3BjzQUnLrbW3SvqspP8Qfu7XJD1vrX2XpB2S/nW4/LckPWytfbekJyV9Jlz++5I+Fy6/KOlXW9xOAJh1dCkBAKB75tNz+Gppd/fOOyX9uSRZa3eHLXaZcPn28DN/Lelfhf/+eZUCwAcl/XdJ/17SRmvtD7zlvy7py23eVgDoGLqUBMdgPjz7CADQm+bTc/hqaTXoO2mM+YGkk5L+D0nXSjrsvX9MUk7SakmvSpK1dtoYY9zvW2svhf9+TdIqY8ygJL9a/FVJV0d/2BjzG5J+Q5LWrl3b4m4AQHv5XUr6+/s1MTExrzIbgl4AQC+YL8/hq6Wl7p3W2tustT8j6d8oaJFbIGnG+0gh/Ouz1lpv+XT4/+JYvfD96SrriP72F6y1I9bakVWrVrWyGwDQdvO9SwnjKAAA6B1t6d5prX3aGHNJQWvdGoWtepIGFbQC5o0xq6y1x8NJWVzQZ40xWWvtjDHmKkmvSzohachb/TWSXmnHdgLAbJnvXUrme9A7n6SlG29a9gMA4jQd9BljBiRlrbXnjDE3SDKSdkr6uKRdxpjNkg5Ya60xxi3/IwXj+74XruaHkn5R0l+F7389DABfNcZsstbuccub3U4A6Jb53KWkVtBLATsd0tKNNy37AQBJWmnpWy7pO8aYM5IuS/rHkvZK+oAx5oeSLkm6L/zsf5L0Z8aYj0k6JenecPnvSvqiMea3JR2S9Ilw+W9K+tMwsHzSWvudFrYTANAFSUEvBez0SMvY1bTsBwAkaTros9Yel7Qp5q1Pxnz2nKRtCev4cMzycUm3NbttAIDOabWVjgJ2eqSlG29a9gMAkrT7kQ0AgBRrRysdBez0SMvY1bTsB4D6zMchBgR9AIC6taOVLq6APR8z4LRIy9jVtOwHgOrm6xADgj4AQN3a1UrnF7DnawYMAJh983WIAUEfAKBunegGN18zYADA7JuvQwwI+gDMaXQLnH3t7gY3XzNgAMDsm69jeAn6AMxZdAtMh/maAQNAM6jsbF208nI+HFOCPgBzFt0C04NJNACgtlYqO+dDYNOM+VKBTNAHYM6iWyAAYD5ptrJzvgQ2jcrn8xodHZW1VtPT06muQCboA9CT6qmRpFsgAGA+abayk54xlVwg7AK+vr4gLEprBTJBH4Ce00iNJN0C5y66GmGu4ZpFtzVb2UnPmEr79+9XoVDQzMyM+vr6tGHDBm3dujW19zZBH4CeQ41k+tHVCHMN1yx6RTOVnfSMKZfP5/X4449rZmamuCzNAZ9E0AegB1EjmX4E9phruGYx1833njF+S/3ExISMMZKkbDab+oBPIugD0IOokUw/AnvMNVyz6LQ0dB/u1X2IttRv27ZNUul+3rBhQ1e2azYZa223t6FlIyMjdmxsrNubAQCIkVQI6NXCAZCEaxadkobuw728D3v27NHOnTt1+fJlZbNZ3XbbbdqwYUPq7mdjzG5r7Ujce7T0AQA6plohYL53NZrL5mvwwzWLTklD9+Fe3ofh4WG5hq6ZmRk9+uijWrNmjTZt2tTlLZs9mW5vAACkVT6f1549e5TP57u9KW1X7775hYBCoaB9+/Y1vA70FhfI79y5Uzt27OD8AW2Qhu7DvbwPuVxOIyOlBjBrrR566KF5lX7R0gdgVsy3loFe7ubSqkb2LVq7Ojo6Whw7kdbjk3a9XJsPzFVpGMve6/uwePHistfWWo2Ojs6LSVwkWvqAhtE60bj52DLgF4z91502G9dnI/uWy+V02223KZvNSpKMMZqYmOja8UHrerk2H5jLcrmcNm3aNKcDkF7eh9WrV5e9ttZq3759DZdL5mo5kJY+oAFpbr3ppPnYMtCNgnG912erra717pv7ndWrVyuTySiTyVR8nsBh7un12vz51qsgbTh/6IR8Pq+9e/cqm81qZmZGxhgZYzQ9Pd1QuWQulwMJ+oAGzMfgpR3mY8tANwrG9Vyf7ciw6tm3uOmxJycnyz7fy4EDquvVCU3mcoEM8+P8EdTOPnddWWs1MzOjvr5S+ON6odRbLpnL5UCCPqAB8zF4aYdebxnolNkuGNdzfbaaYfkFlmqznkV/Z3JysuLzvRo4YO6q9/qm4N2b5nKBuh7zIajtRe66mp6eVl9fnzZs2KCtW7cW32skHZjL5UCCPqAB8zV4aQcK+J1Xz/XZSobV6AQu1X6HQjc6oZ7rm4J375rLBep6pD2o7VVuQjHXqudP3NKJni69iqCvR1Eg6l0EL+hlta7PVjKsRgos1X4nn8/r85//vKy1Msbok5/8JPcU2qKe65uCd+/qRoF6NstbaQ9q57Lx8XHt3btXGzdu1Lp166p+dq6WAwn6ehC1kEB9qBxpTrMZVqMFlqTf2b9/v6anp8teu642vYjrbG6pdX1T8O5ts1mgnu3y1lxuJZrLJiYmqk7aMj4+ri996UuSpGeffVb33ntv1cBvruYJBH09iFpIpE0nEkgqR2Zfuwos7rl9Sa97CddZ+lDwhtON8tZcbSWay/yKHmutjh8/rtHRUa1fv165XE5jY2Nlnx8bG0sM+uZynkDQ14OohUSadCqBpHKkO9pRYFmzZk3V172E6yydKHhDorw1X7iKnn379unxxx/Xj370I0nS448/rk9+8pMaHBws+3z0tW8u5wkEfT2IWkikSacSSDLr5vRCt5Tx8fGK17XGUCTp9P5wnQHpRXlr/sjlclq6dGlZzxJrrSYmJjQyMqJdu3apUCgok8loZGQkcT1zOU8g6OtR1EIiLTqVQJJZN65XuqWcPn266ut6zcb+cJ0B6UZ5K1mrlWq9UMkYVSgUyl5PTU1Jkj71qU/Vta1zOU8g6APQUZ1MIMmsGzNb3VJqZfQ33nijnn/++eLrzZs3N/U7s7U/XGcA5ptWK9V6pZLRbcuuXbv09NNPly231mp0dFSjo6Patm1b3eubq3kCQR+Ajms0gezF2sE0aFera7XzUyujz+fz+va3v118bYypOn6i2m/O5W42s4H7CECzWq1U65Wxb+4RQf6M0VKQ92QyGV2+fFl9fX16+OGHlclkJM2tyVkaQdAHoKf0Uu1g2rSj1bXW+amV0U9MTJR1r7HWat++fbrtttsa/s24/SHQCXAf9S6uUcwFrVaqtfL9fD6vffv2yRhTnGGzWRMTExUzRBtj9JGPfEQ7d+5Uf39/MU9yAeBcmpylEQR9AHpKr9QOzmXVCpWtdkupdX5qZfRxGb8xpunf9PeHQKeE+6g3cY2i1/n5RyuVhM1WMkZb5h577DFt2bJFixcvbioAHB4eLstjMpmM7rnnHq1bt07Dw8PFtPIb3/iGJGl6elrLly9v6DfmCoI+AD2FLnut6XShstb5Scro/YLEPffco4ceekhSkAGvX7++pd90CHRKuI96E9coellc/rFp06am19dMJWO0ZW5mZqbiEQuNrDOXy+mTn/xkbMuh2749e/aor69P09PT6uvr0+TkZEPbPFcQ9AENomtOZ9VbO8h5iNfpQmU95yea0ccVJD796U/Xff7qvSYIdErm8gxzc0Gz6Q/XKHpZL1RKRFvmfO4RC820OlYbQuB+M+33JUEf0AC65syOWrWDnIdks1GobLT2Nq4gsWnTpoZra9sVHM4Xc3WGuV7XSvrTK9colWaI0wuVEn7L3Pnz57Vr1y7NzMxICoYCdCpP64X7stMI+jCvNZrxuW4HrgsAXXPidbpA0Qu1kfXoRsGqFzOv2SxIEOig01pNf7p9jXaz0oxgs1yvHY9eyT/8lrmRkZG2TeoiJU8Sc+rUKR0+fFjLly/viXPRCQR9c1ivJRZzTTMZ3/Lly4uDi9M82LcVs1Gg6IXayFq6WbCqt1DZaBrSbJrTKwUJoB3mQvpTTbcqzXqxh0Y3y1G9eDyk7ldKRNXqmtmI6CQxbozgqVOn9KUvfUmS9Oyzz+ree+/VunXr2vKbvYSgb47q1cRiLmkm45ucnJwXg31bMRsFil4NIvwCRK+3RjaShria0dHR0eJYi0bTnF4rSADN6tX0p17dClp7LU3sdjmq147HXFdPAB99ZFChUNDExIQOHz5c9rm9e/cS9KF3kFi0rpmMb74M9m3FbBUoei2IiBYgtm3bJql3WwPqTUPcfhUKheK4ilbSHHooIA16Lf1pRLeC1l5rIe12OaqR4zGb6WY7n5E3W9tTbwC/fPnyiqBv+fLl2rhxo5599tni8o0bN7Z5L3oDQd8c1WuJ51zUTMY312t4q2lXpjKbx6iXAohoAWJycrKnr5VGH4PgAr5sNlv189WMj4/r4YcfLr6+++67U1mbOh/Uuvd66d5EpW4Erb2Wf0bTwOXLl2vPnj2ztm2NzFQ9Wy2SSd0fuznhUD3bU28APzk5KWNM2SMhxsbG9MEPflAf/ehH9cwzz+iWW25Jbb5E0DdH9VriOVc1k/H1Qg1vuwtU7c5U2nmMkva1211zouKCqF64VpLUm4b4+2Wt1W233dZU7W8+n9dDDz1UVsv68MMP61Of+lTPHiPEq3Xv9dq92QqC1/aqlibO9rH208Dly5frK1/5SvG92bpm68kjZrNFMvqMvGYfkdCp7XHdMaPbU28lpuut5a/z4MGDOnTokKRgdtCdO3em9n4n6JvDerlAic7pRIGq1UylU5l1tX3dv39/scthL3Rxjguier3A6LbJnf+4bWy1gsl1zYmOpXBGR0e1devWnjw+iFcrveh2t7l2SVPw2uu6daxdOWrPnj2Sun/NxuUZs9mzK+4ZeVNTU8rn8105HtF9dd0xo+rNp3K5nO65556yCshCoVAMAq21dZ3/Xs/bkxD0AXNMJwpU1TKVerpxdSqzTtrXfD6vxx9/vNjl0FrbE12c/YqYuVBgrHcbm61ginbNiZqZmdG+ffu0f//+njw+iFerEJqW4QdpCV67oZnHIUlzY3xdpySlx7PZsyuXK39G3tjYmEZHRzU6OtqVNDqXy+l973ufHn30URUKhaoT6NWbTw0ODiqTyUgKAr5MJlNWIVmrPDEX8vYkBH3AHNNK5pSUESdlKvUkbo1MCNJoppW0rxMTE8XayGw225MtRd0uxNSj09sY7ZoTZ3p6umePD+LVKoSmZfhBLwQCc1EzheJuH+teuGarpcet9OxqNO/N5YJHJOzZs0fGmK7kYf42r1+/XqOjoy2NJ/fX+93vfleFQqEYRC5btkynTp0qfmbdunVV93Mu5O1JCPrQM+Zqc/lsazZzqpURx2Uq9SRu9WTWzdaMJe2r+42+vj5Za7VmzZqa65pt3S7E1KPT2xjtKpTNZnXjjTfq4MGDxVZaqfmW2tmeZY40qqRWITQNww96IRBoVjev1WYKxb1wrLt9zQ4PD8taq2w227beK620SjWzPe247uK2udkyT3S4RVzPk3e+8536/ve/X3y9efPmqus8e/ZssRuo1Jt5exKCPvSEudxc7sxmJttM5tRMRlxPUFBPZt1KzVjcvuZyOW3btk0PP/ywjDH6yle+0nPXTC8UYmqpdxvjMs969ivaVWjx4sVavXq1Dh48WPa5uLF+tcz2LHNpSKPSqpNpb7cDgWZ0+1pttjKpncd6LlfQFAqFYqtWq1rJe0+dOlVMm6Pj/OK067qL2+ZNmzY1tK64bYn2PDHGaPPmzXriiSeUzWZVKBT0kY98pGLmTnctRSf72bp1a0880qIRBH3oCXO5uVzqfiZbj2Yy4kYGR1fb3060KE1OTiqTybTlmulUAaEbBcZ698X/3KZNm6p+Lvr8wUZmucvlctqwYUPZOu644w5985vfLGbAmUym4fM327PMzfU0qtu6MdnTfNXta7XbFV5z9ZrYv39/sRJrenpa+/fv19atW1taZ7N5bz6f18MPP1wM+upJo9t13bWjvBDdln379klSRZ7hzMzMqK+vT4cPH04c4lIoFGSM0fT0dLH1cy5cVz6CPvSEbnaFa0dhpNuZbD2azYjbEbh0ohDQrmtmrhYQ4tS7L43sc/Ta3rt3b9nrffv2aenSpVXPa3QdkvSRj3xE3/rWt2SMkTGm4fMX7TrazDrq4dfySr3dXbdX1XO9NZsOz4W0d7b1QtfybraQdnKcebvE/XZ0/PPU1FTLv9Ns3uuPm3fbVus6atd153ry7N27Vxs3bmw5cLTWanR0tLg/buKWbDar06dPy1qrvr4+TU9PV0ws5l9LfX19xSB4ZmZGo6Oj2rBhw5xKbwj60BO6VTPYrgJ/L2Sy9ehkRlwrA233b7frmulEobFbhYl696Xa56LbHh3XsXbtWu3du7c4ntLPTJPun2gGfPz4cY2NjSmTychaq23btjV8nPyuo50a0xfXyjk5OTknu4x1U63rstVxR1JwbRUKBR08eFDLly9P7cOV69Fst+206OQ483ZI+u0NGzaUzUq9e/dubdmypS2Vro2uw1WquXT+7rvvnrVxmePj48WhG/v27Wvq2bD+tkxNTWl0dFSXL18u5mPZbFYzMzMaHx+XFEzeMj4+XjGxWPRa2rJli8bGxjQzMyNjzJyrZCLoQ8/oRs1guwr83e7O0m2dykBnI5Bsd8DuH4tWHmbejHr3Je5zblKUaBDns9bq29/+dvHhtiMjI9qzZ0/N+8fdH279Tz/9dLHGtL+/P3EK7lpyuWCWuU6Jpg+Tk5NVu8IiXq3rstUxv9u3b9euXbv01FNP6fnnn9fzzz+ve++9d94HfrW6d+/YsUPW2mKhfraPVye71XdynHmr4roeut4S73vf+/TYY4/NWlBRbUZvv7Wt3muj3jw56Xddt1J/oq/HHnusqUdGuG3J5/MaHR0ttua58XvZbLYY5K1evVqHDh2qSKOix2FwcFB79uwpPvKhVyv4kxD0YV5rZ4G/m91ZZlNcYt2p1rLZqIltd8DuHwup+QyrGY2MwfQ/J0k7duwoPuxeUvE8SqoYxzAzM6P+/n4tXry47tndcrmcli5dKql84paZmZnYh+32grnSgt/ral2XrR7nXC6nCxculC3bu3dvYkE1rS1cjXBjYt0Ysoceekjvf//7Z62CqtPpe638uJv3drWuh9u2bVMmk5mVoCLpHEQrANv9HNVq5z7arVQK8ohmxn07Lv0ZHR3Vvn37ite8e2SDJG3YsEEbNmyoSBfy+XxxDLs7Dq4Cs57JbXoNQV8PIkOaPbPdDWaun9ukxLoTGehs1sS2M2B3++66j7SaYTWq3n3xP7dnzx5JKgZ8cc9DcgUU929JDT0qw011HTdTZy/OvirRgt9O1a7LdhznjRs36tlnny17HacXx/DOZr7gj1H1x5AVCoVZraBqNX1v9Zj5vQ9mu/Ce1PXQ9SaYrTQn7hxIlRWAfX19TeVfSeeo2rn3u5W6B6e789NquWLlypUVD2GfmZnRrbfeKqm8ZXDPnj0aHh6O3dbh4WE98cQTktS1h9Y3i6Cvx/RihpR29XaDcZo9J90+t52csCbaBaId+9XMM4J6QbQrY7syrE6K1jxHu6RGWwV37dql06dPa3x8vNgKWGvChM9//vPFQqY7p+4BubMZFDdqvrTgd1ur3cLWrVune++9t2Z3tF6b+GU284Xob91xxx165JFHivfibFZQtVJR2M5j1q3Ce7TroX8c2pnmVMv3486Buz/87pXT09MN98aodo6qnfu4Xij+v10w1mgFgT/kwmet1djYmPbs2aNt27bpyJEjFS2v0W3ttTSkEQR9PaadF9Ncb1Vqt3bNDlfPbIX1rGc2E4pOT1gT1wXC7x7RzHFv9BlBvcSNNYvrLtJLxsfHi4XkarXLfiFkfHxcTz31VPG9vr6+mgU3v0uNJL35zW/WwMCAnn/+eUnNFSragTSy/Zp5ZEi9x75WOrZu3bqaY4+iadjy5cubKki2y2zmC3Gz6H7qU59qawVVI8/wbLZFq13HrJn1tDvNiAtyGrkeq21P3P0iqezzSefA9VSRgjS+0XHX1Y5trXMfDXpdcOwqDo0xDT2T1e/K7CYP87nxkw8//HDxtRSkEUeOHNF73/ve2MnC5mK3f4K+HtOubnLdblXqNdWOR61EvFr/+2ZnmfNfd0J0n+rJ3OrNzOISwKT1Nzupyfj4uB588MGWnuPWC3q5lWh8fFxf+tKXJEnPPvus7r333romKXGPbHDWrVunG2+8sep1Ew3af/rTn5a9zmazDRUq2lHwIo1sv048MsTXjsK+X+CMPmw5rlDcabOZL8T9VjsrqBo5/+63mpkYqV3HrNEKgE6lGX6rXyPrr/X5uApr17Lpfz4aYLXaU8V15bfWJp6jRvNG/xmG7nW9zzBcvnx52Ti+t7zlLXrhhRfKep64Cmb3f9cbxT8G69evL277XO32T9DXY9p1Mc3l5udOqCcokeIT2Wr975uZZa7TCUXcPtXKJOt9jpb/GZcA+uuLrr+ZSU3c7F3Rh6jOpdq0uWD37t1lr6tNfOGLjp3avHlzze+tX7++OBV5tJZVauz81lN7XQ/SyPar95g2e+zbVdh3BU43lrVWobiTZrMAWe23mq2g8gO4eisXWw2c2nXM/PVIKj4mwBgTu12dTjMaXX+tz0fvFxe81LP+pUuX6q677mr4ETXR87t169a2TA4UzTdeffVV5fP5utY7OTlZbLnMZrNas2aNDh06VFznli1b9NRTT5UFge973/skKbG818sVutUQ9PWgdlxMvTDrXC91naonKKk15Xwul9P4+HjZjE/NzDLX6WMRt0+bNm2qmknWcxya6a7RzKQm7nd8d9xxh6Tm+vPPRZ2+d/L5vA4ePFi2LGnii6h6x05Fbd26VSdPniwLGJ2bb765bD+r7X9c7fXo6GjD3X56IY1Mm3qPabPHvt0BUrVCcV9fn0ZHR7V169ZZCfxmK01r52/FPcdSqn5eG+l1snz58sSgo1374dbxx3/8x8VWnqSJSzqdZjS6/lqfj+s6Gh0/GNVqUB49v0uWLGnLedqwYYNGR0eL48APHTqkF198sa7tW758ebHLpj9W0XnllVfKgsoNGzZo69atseMtpd4q2zaKoC+lut383Gtdp3K5+IlGGklk3bg194yyu+66q+6C6mxK2qdqmWQ9x6GeDCaplTTaVaRaN5roerPZrM6ePZs4tXQvHPN2avbeaeRYTExMKJPJFMcy3HrrrQ09o6uesVOO/6DduJk7pWDMnytc19r/6HV4/vz5sm4/7mG+tXQ7jWyXdt4DszUjYivHvt7Cvpt2Pm4sTtJ2SCp7nte+ffvaNl19GtOqaAG/npknh4erT9DlPz9wenpafX19FS1v7T6W+/btK0ubCoVCbB7Y6TQjqZxS7fO1tid6v3T6+YXuuLnZN9s1VjuXy+mTn/ykvvvd7+rgwYM1Jw/z+S19kvToo4+WvX7llVfKPv/6668XfzN6vHrh+ZatIOhLsW42P7dzDFk7JE00knRTx22X2yeX2PhjkDod5NZTgHGayZjqzTyayfByufIxI3HjaKKZuZtVznW1ieuWIqnpgd2+XiuMNTu5QCNdHqOB05YtW9q2/dHt8h+0mxQI+A8hrrX/0etw165dFeuq11ztouO0M93p1IyI27ZtK2utaXU8Vz3cpA+uMuDxxx9PTB/iCsX+87za0Y2v1ypBfa2kf0ljBFvZNz+fdf+vNiQjen01I5pm3HrrrYnranX/ak28kjQhWpJGt8d93n8sQbVKtUYnOnKBq6voa/fjeA4dOlQM0GsNC/BbjH1uMpdMJhNbEfn6669rz5492rRpU8Xx9SeFkYLnW37605/umfu5FoK+OabXCqhJ2jGGrJ1qdU30g45mphnuZF//RgowTjMZUz3faaSWPXqduu9Gx9HEZeaFQkGrV69Wf3+/3vOe92hwcLCim0V0Rsh6W3ii29lrhbFmuhBFr79du3ZpbGwscXxKKzXWcee2WkVJtEDlavhdpiuVZ9717L9fcPHHJmaz2bKxpmnnn/dsNtvUPRC3rnbNiNjX16eHH364eJ4//OEPl1XmdOp+cwUzx1pbd8VjLpfT1q1btX///rZ14+vV8aOtpn/NpCPuWMzMzMR2o/RbilxLn7886fqqZ6KwpHTKjTl2FYgjIyN1H4NGNDrxSqeuk2rb4bc2rly5suY4xziTk5PKZDItpUv+uZJUnFPB5SfZbLZq1+voJHI33nijnn/++eL3t2zZoldeeaWilc95+umnYyulhoeHy7qIFgqFhiaV6TaCvi5oNnDrxQJqklqZQdy4nGYeg1CvegvSzYxba2T9zai3AJNktisK6ume53fvcTWJU1NTZTVoLjE+fPiwPvWpT1Uc+2gw0cxjHXqxMNZoQSo6U5q1Vrt27ao5PqUZSS2KtSpKfG585vLly/Xwww8Xn9Pn1LP/7pqempoqWx43SUyauXtJCgrRo6Oj2rBhQ1Pnul1pmL+eQqEgY0yx8PfNb36zuL3R6zIpnWom/RoeHi5LD4wxDVU8NhPMNPo8tF7QjvSvVstRHL8VL9oK4x/7uDF9SdeXVH2isFrn+5Of/GRHHtTeyEQ3s3WdVNsO19ro58VS9XzEPfpn7dq1koK0vZV0yVV0uzkAXNDp1umOz4YNG+raR0nFxwO5B7KPjY3Fju9zjh8/XvdEMXMp3yHom2WtBG7NdvvqVstgtVYhP3Fr5TEIjWxLPZl4M+PWGll/M+opwCTpRkVBIwG9tVZf/vKXi+O94hJhl2msXbu2bB2udtYFN6tXr254W2crk230PmykRTU6U5qksuOSNG6mma6xcWmQk5QuXX311cUA3lqrb37zm3r729+uw4cPlw2u37Vrlz784Q/X3P9oDa7fPWeuPtqjWblc0HX6scceK47PbHb/k9KwZq7d6CMRXKuNz12Xrut6XB7QbPoVLcTHtf7UaiVtpLdEre3sZP7Qinalf408quGRRx4pvk56VEu1Yx93fSVNFFZPwOV3AWz3g9rjuqJWG8/YTIVfM9dUPb2Wku7XqOijf7LZrDKZjDZv3lxW+dhIujQ6Olr8fb9MYIzRzTffrOHh4Zr7PDw8nDiG3O1fNMBftGiRzp8/Lym5BW9iYkLZbLa4fZlMpmrw2WuaDvqMMVlJ/4+kWyQtk/TfrbV/ZIyZkuQGWXzLWvt/G2P6Jf2ppJsknZb0cWvtMWPMCkn/XdKVkl6VdJ+1dsoYs1bSn0taKOk5SZ+y1iaH5HNIKzVrjSbQs1ngb6Vg0MpjEBrdvuXLlxfPQbuDt0YK6o0eq1oFmCTdaMlKCuhd9xspSLynp6eLmZ/7d1If+2effba4//54zLvuuqulsQOtFsbqOZf1Pg6jmW2Int8lS5ZoeHi4OBlFoVCI7arUyjOPXMHKDdIfHByUVJkuuf12Na2OtTZ2Bs+xsTFt2bIl9tj41350n7ds2VLWlbVXWlFmy/r16zU6OlpsLW1l/6NpWCtBl/ucGyO3d+/esrGdd999t6Sgldiv8PHTqVbSLxcQJ6nWStro/VjPdtbbItbOFs9a2hWM1nue4rp7N3O9Rq+vuGfK1TOzaHRIgcuX4vahmeMfPS5HjhxpaN+qaaV8V+28R7vXujw6qctr9Lmt7j4+f/58MS+Pa9Gttl9x+YMU5B0/+clPirM91zon1Vrg/IlcHBfwOdGeJFLp+Lj09p577umZSpx6tNLS1yfp29bafxYGgE8bYx6S9FNr7fsjn/01Sc9ba/+BMeZXJP1rSZ+S9FuSHrbWfskY888lfUbSv5f0+5I+Z639gTHmP0n6VUlfbmFbe0YrNWuNJtC90D+8Gj8TrDWNcD3bkFRD7WoDq80GFl1HJycYaPZYNTNWp5HrrV2FiqSAXgq637iM2QWF/r9dwT2uxc9lxn7L4dGjR8vea6V7UqOqnUv/WO7fv79YqE0qTDSbeccNup+YmNCHP/xhHTx4UOPj49q9e7fGxsbKZhmLZobRzC3uWhgfH9c3vvGN4mcymUwx0I5Ll6LdkmuJa6WKG8961113le3zli1btGXLlp5oRelGz4pOtiK1q/ufGyPnKn/uvvtuDQ4O6rvf/a5mZmbKHogsla7retOvZo57UiuplNxdOUkj21lt3Unvd7ICt9H0L+5Y17v/rtdKX19f8Tpw+9dMpabb/riHy0fHjsfNLOp/xlWSxbXCNXv8o8fF5W+18ivXXbLaI3GavTdrlXP89ERSMR/Zs2eP9uzZU7Hv0ee2SkHgt3fv3mLlYFKLbpz9+/fX/Mzu3bs1ODhYc3xktBLZzVQ9NDSkZ555Rq+++mrVPGrJkiWxy/0x6a7Sc65oOuiz1l6U9Lfhv2eMMS8qaPGLc6ek7eG//1rSvwr//fMKAkBJelBBq9+/l7TRWvsDb/mvKwVBn7vZWpltqpEEera6rtUq1DpJGXM7WluqjTPya/Ck+AChkRnBWinYzWbLm3+9HTlypOpYhXYXKqIBvd/9pr+/X+9973uLgZtUmmVSCiZkefTRRysSY1dQ8FsOXf98afYf4J50Lv1HFLjtqraNrbZmRLs6ucoNfwyEFDx4+FOf+pRyuZw2bNigxx57rJgh7t69u9jKljQldfRh7u677llm0QKE35JSr7hjEx3POjk5WZxoYO3atU0XFuvRyL3eiVkF69VsxUUt7cpDomm8pLJgXio9ENk/j/XkDfUEUkktZ66iyd+/Zu7HevOwWutOer8bPTaSKlLjjnU0HUrqTRN3nJqZqKzaRGGuJdW1LFWbWdSlUf7ja6JjjKXm0+i4696v4I6bGTPaXfLee++NDfyauTfrzefdsmqt8G59k5OT+uhHP6rDhw9LUlmLvssjqo2di57LevKMBQsW1Dwn7nj4+WBfX58WL16snTt3qlAoVP2tvr6+2EnB9u/fXzYs4Xvf+16xInIuaMuYPmPM1ZJWWWsPGmMWGGN+IOkVSf/CWvuypNUKum/KWjttSqXPPmvtpfDfr0laZYwZlJT3Vv+qpKtjfvM3JP2GpOLg0V7WjbFV7agBrlXoyefzevzxx2sWvOsZ89BIoOiLu/kdV4NnrU2cDSy6jmw2q4ceeqg4gDjagtPKeXSZTFKf/naJjnuSgsQvaaxCO2oNkzKPuO430UHd/r9vu+22iod4v+Utb9FNN92kY8eOaWxsrNjtxKk1k1cnxGW6+Xz5Iwr8wkMmk4ndxmYL1tEaW1dr7QpP0Qwt2pIWfd8vYPqD+B9++GHdcccdxYHwvkKhoL1798ZOL57L5XTHHXeUtQ4mMcYkHpvoeFY/uPWvkXoKi41ICn6T+PdQdNbKufpcyUbykHrSArd8z549ZdefMUa33XZbbBfjWgFttbSr3pazrVu3Fgt40UmRpqam6prQoZ7Au9a9nvT+bFXgOknHrdqx9gOF6Pd80eMUV7FTLf+p1cPCjVW21uq6667TqlWrio+kietW648L9rv7+mM8ax3/eu/ruEo697tu5tFod8m9e/fGpjvNlO+iaZSrsIv7rvusy8uirfBJle379+9XJpOpGBN4+PDhiorBuHWsWbOm5n5ceeWVdd8T7py67XdBYLVAVJJGRkZij0s033z++eeLj3eYC1oO+owxiyV9UdI/lSRr7U3h8l+U9ICkDykI7vwj5a6GYqnNWmuNMdOSFkjyz0Yh/Ctjrf2CpC9I0sjISM9PnVNPobpTffabXVe1DNNtp99Hv1rBOxpUuQQ1us/RaXrrCbCWL1+uQqEQG8y5BOGuu+7SkSNHdP78eS1evLiiVSDaj11ScZ3+uepGjWszosdbqt4Fsp21htGuKblcfPebahYuXFj2+oorrtDw8LC+/e1vl1UwuK5CxphZH0wdl+nu2bOnLEhxhQ8puJ7iMrR6WzOi90n02PtjDaJdWrLZbDFg2rNnj44fP16WebmHEbuZQKMZYrXAzdWQRwsQ0UkbqrHWJh6b6HhWd23HTTTQzvsxLvh1LaVx/HvIn1XQr4jqRMVfta7t7chL6slDGq0Miwbz2Ww28f6ttS/V0q56W85cNy5/HzZv3qyxsTGNjo7WNbFHPce81r0e1zLkApV2Bd/1fCbpuPnHOhoQu14d7p6pN3+Mq9iplv9Uy4OjY5VffPFFvfjiixoaGtLOnTsrKnD8CuIof5uqnbdq5aSkCYpcXuH2QyrNPPre9763bDs2btyYuI3+vVnPeXdlJTcRyb59+yoq7Nx6JJV1dx0ZGSnrDRJ3rjdt2lTWNdTPNxYuXFhReZJUYR833s5xLXBJrcbudfRaKBQKuuOOO3Ts2LGaAZ8UTOoSZ8OGDfr+979ftuyZZ56ZH0GfMWZA0sOS/j/W2rJOvdbavzHG/F/hy7wxZpW19ng4/s+dCWuMyYbdQ6+S9LqkE5KGvFVdo6DVcE6rljFVSxy6KemGrDY4Oinj9rt6uUHza9asKXtI97Zt28peu1rfas96yeeD6YVd7c1dd91VPG7RzNNfd7TZ3iUg0QkH/NY4VyCu1u+/nlbJevr0N8sfxyhVjpuTkp971kqtoduXU6dOVXRNGRwcbLgL3uLFiyte+xUMjjuWV1555awG4EnjItxU1S7Q3rhxo5577rniNbN3714NDg7WrP2O/la0UBE99m6c47Zt2zQ+Pl58YLkxRlu2bNHixYu1evXq4j0QDZiuu+46nTp1qtiCFq15r8bV6kYLEH43mFqMMYljPlylQVTcjJCttoD45zXaPbXWzJhxtfh+4diNVWlnhVGtru1uWafvi0Yrw+KCeSlorfXTiXqCyWppVyMtZ9FWEDfjbD371EjQWyuIdu/HtTTXKljWO2lUrRbsasGd33PD/bm82x8376+nmrhroVaFgdu26G+cO3cu9jvPPPNMbAVONOCUgvQsk8nElhGk0rVerSJYiu8a6Y9Hd9vtD30wxujxxx9XNptVoVDQRz7ykaq9C5x6z7srK83MzBQDv+hMpv52u3JVNpvVnj17tGXLlrLrxz/XfldV/zp9+umndeLEidgxgY1UNg8ODuqmm24qm+zLPwenTp3Sl7/85WJlcPT82XDm6GiaHtcjplolVC6X0wc+8IGywO+WW25J3O5e08rsnX0KxuB9wVr73XDZMkkXrLWXjTHvlnQ4/PhOSR+X9EcKxvd9L1z+Q0m/KOmvwve/HgaArxpjNllr97jlzW5nr0jKmKI3mVTZb9o3W92DXIDjurlIlRljNpvVkSNH6goWXMHNHzTvujG4xDL62i98zszM6PHHH6/oFujX+rvB2v5vus9GB3W7xDf6HKC4CQeiGbD/7Bj/eNWT6Xeym061MUWS6jpHjdQgx+3L6Oho2Xd2796t8fHxquM14q7paKvPmjVrNDg4WNE65Vq0Tpw4UaxVrFYwasf9U61m16+AuOOOO/TII4+UjWuIq1mtJa5QES2UuePuWpjcb2YymeJYPL8SJeqnP/2pXnrppYpJdFzm95Of/CRx+4aGhnTixImKAkTczGdJMplM4r0QPWd+wfPkyZN67rnnil20du3aFTsDaD3izuvdd99d9nDieu/XwcHBisJxPZUvSfse97wyqXbX9lYf2F7r951m0jU/mE8a11VvMJmUdiXlu7lc6QHUGzduLPuuq0w4evRo8QHiUvz4K6cTPUAabWmudzvqWW9ScOfSraVLlxZbsvv6+vTYY4+VBQEbNmxoqLu9uxb8VqZGW0vz+bzGxsZiv3PLLbeU9Towxmjfvn06d+6c1q5dq/7+fl2+fFlLly7VlVdeGRt4JqX71SoQ/K6RhUKhWKnhho1Ehz5EZxCtV73nXVLxHEXLdu4z0THobj/8iY789WzYsEEbN24sq1R3lU9u7Jw/nj/aJTjuXN52220VrWmTk5MaGxsr9h6KnhN/QiipclZRf3+c6667Ti+99FLZ8quuukpbtmzR6Oho4kQ6t912m5YuXapnnnlGt9xyy5xp5ZNaa+n7x5Lep2Ac3r8Il/0rSf/BGHNa0lkFM3RK0n+S9GfGmI9JOiXp3nD570r6ojHmtyUdkvSJcPlvSvrTsCXxSWvtd1rYzp4RlzHV6jfta3SMiftOo4XcpPEO7vvRFrsNGzbUddFHpxbfuHGj9u/fX0x4oq83bNig8+fP60c/+lHx9/xneUnJ46qi++x3AXWJr1tndDbPajMR+l0/s9lsYnehaoWTdnbT8UW3YXJysuy81Aq0qknK8Fym5QLg6ExeK1asKEtQ3TkcGhqq2oV3cnKyWANqjNH4+LiGhoaKXa6SWpCefvrpxGuxXeNq/WvB7/4brYA4ePBg2Xa6FrFGC4Vx17h/7I8ePVrxW44LjP0W37iuM9HWPfc5Y4wuXbpUtbvNVVddpXw+X1GASJr5LE604O0knbNTp07p8ccfLxuPI0lPPfWUdu/eXaxYaOQ6j7uHN23apE996lN136/RbfULx9EJjGptT1yNenSMcVKwFZdGN3qtJ9Xou7FHcUFCs91M3T3lFAqFisoNf/+qbXNcgJfU6iGprBLG9fbYt29fcdzw1VdfrVtuuaWiUOtfX65nhctf6p2evtp2N9rS7L4jVT9e9a43l8sVK7Ci6VZ0OIQLkP28vVbwFncMag0nqXZO/Z4grrLKGFMsuC9fvrxsgi1/IitfNpuNncAjKY+vlqe7dHdkZERPP/102Sy17vNLly7VXXfdpcnJybIeAlL9lcL1nnf/M+43q11zPvfYhegjerZu3Rp7bKampsoaM5LKtv65dL3eHnvssYrfd+t58MEH9ff//t/XunXrir1Jqj2Pz82wmc/nK947fPiwbr755rJKzddee61Ygfzss8/qox/9aHG7/XO7adOmORXsOa3M3rlD0o6YtyraOa215yRti1l+XNKHY5aPS2quarJHJWV+0Rr7uAzVabTmr9lCbtx4Bz+xbfZhwH7i6GqOozPcRRPPaDe/6LO8ot+RKoMIScUWGJc4+IlENEOLy1CWL19e0ZWsUCgUu700Ujip1aImNX7uklpm4/izS8Y9uiJOtaA2+kDbj370o8UasOHh4bLaV2utnnrqqeIz+fzWJ78FVlJZbeNTTz1VLHS62fbiHuZ+9dUVcz7VtQ+N8K8F//lDLsN0XX9XrFhR9j03mZBbh2s1cNuWVDCuVqh44oknag5K9yfP2bBhQ+LsqO6zbh9uvPFGjY+P64UXXihWmLggy//uypUrY8dWNNLS99xzz8W2DCS1ZPmT5US5sX1SfFqQNAak3gqkJLVaZKXKCYzqWV901mG/i1i1mvJWH9ge9/tSaexRrcm4GqmkjKZVLnCqp5LMbx165JFHytI1tx/VWkijE1ps3LhRe/fuLVZ0vPbaa8VWIldJGHd9ffjDHy7+fr3PDK017qtWS3NSK3it9KSeFuxqk7TFBcjuM9ZaffnLX254qEq1bpJOtXVF77Wbb765+MgaSVq3bl2xAmdqaqqiJcmZmZnR2NiYPvShD1Vdv3/Motd+9Dz4Aan7jRdeeKHiem2kUthX73nftm2bdu/eXZE3+Z9x14akirT+6NGjWrduXdUgVwryN3/8fdzMvFF+r7dqQZy1Vg8++KA+8pGPJAbuUqmcIAXnPi7om5mZ0XPPPZf4W5L0rW99qxiwztUJuXxtmb0T1VUrwDdykzda89dMIbee4KGVhwG733czbBljyrr7RRPP9evX69FHHy3e2HH77H/H78bpuja5YM/1Y48Wdv3xB0k38+TkZMUEGa5bnSsAtTpTqq/ex2BItVtmo5/1C8zGGH33u9/VBz/4waZqkKPX2L59+4pB4Le//W3ddtttxVrOaIufGyvi1httgY1yhV7XWjI1NaXHH3+8WODwg8hG9qFRk5OTZTPBTk5OFgtvbh/dte23kLmA6Rd+4ReK41/c9OC1CkhJNdvuuPjXdTQTzOVy+tCHPlTMrM6dO6crrrhCp06dqvgd17onBa20fkXHlVdeqS1btuiRRx4pOz9Lly6tCKR27NhRUUlSjetuFW0Fi5ukye9ilLSuaFf06LUplRfS/e5W1SqQGr1Hmi3E+evzrzWX5sQFCL52PLA9+vsu/XMtOrXyk2gl5UMPPaRPf/rTid9Zt26dDh48WDzfrqu+2798vvKh5tHWSKevr0+7du3S2NhY8fz6FYxu39y4JjcDrbsmpFJvDnd/uWveVfREr6/Dhw8rk8nUnd8mDe3w7wM/UHHb7FcWJT0+odbvTk5O6u67767aZTfachatlMnlSsMh3PHx079avRqiee3y5cuL15YLMOspw/jr8SuV/Xzu+eef1wc+8IHikA5XxkkSlzY2ei/XOg8HDhwo/tu1/Ekq6zlTTdyEabUqRb71rW8V8wdXkRqt+F23bp3uvvtu7d27V9baslYwd8zcb42Pjxe7Qbru0itXrix295WC9HhkZKRsEq6k602q/ngHfzu+8Y1vxB4nd7/fcccdkkrp2FNPPZW4rlr8yqG1a9eWdRWup8ddLyHomwW1Ei7373r6sjcyxqSZrjHVgoe4xLXebkr+Z/2aQUlVx5zkcjndc889FftcreU0Og7Q/VsKbnA3UNuNu/KPjf+YA7/VdXh4uCLo87vOua5gUu3zWEu1GtY41Vpm4z4bnV3ywIEDOnToUNXp7pMyvOg15tbtz0jmfieqUCho9+7dxZlVq9XaSaXuIa61xM0g5sZL/MIv/ELVY14r06639m54eLisFnH58uUVhTdJ2rVrV8X+GGN0+PDhiq7CkmpOoR23HVLp2PsFVt+JEyf0la98Rdu2bdNDDz2UeIzf9a53lT3kfN++fWXvHzt2TN/+9rc1PDysn/70p8UWwUceeaTs0QSusF9PZuq4boh+MCOVt9C7addd4dDx70tjTNlkTv7x8a/Nvr6+skH9rvVm06ZNsRVI9U5OkjR+rJm0wF+f6xkxNTWl0dHRtnYjr/f3x8fHi0GUVGqtThrvNzw8XJFe7t+/v6JiZnx8XA899FDxmnEFUT/NS6o4jbZGOtPT02X3XzabrXiExrZt2/Tggw9KKuUP/jXh0pv+/v6KguiRI0eKEz0kDU+old9GC7mu4iYpqI/Ln6XGK3WbbTmLm9jCXSN+a2U9Y1fdOZeC+/euu+7Sl7/85bL7eP/+/Vq9enWxAi0uH4zbH/f4mmg69/3vf7/sYeHR/Nx30003xS5v5F6O5ieu7Bb3fLiZmRmdPXtWf/zHf1zcpmqPoIk+yy+pC2JSpYgTN5GLO5f+feAqJ/1rILoNrlIqbujA2NiYdu/eXXFdu98zxmj16tWSSvdbtbKAv+64ZcYYPfLII7r77rslBffa29/+9qpj0+P4vcNc5VD0QfT1jLXtJQR9s6BW8FUtIY4mHNGav1YKuVHVgoekxLWWuO9Fa2fOnz9fdR1un13i4GYZ9NfpF7D8rk1SZcIQ15ddUsUUyo8++qgee+yxYk3OXXfdpQcffLBsfX4/9XaOGatWwxrVSHDvZpeMzlrlusTVup6i70evMUkVD2N3rUdJCfTk5GTi+1Hbtm0r24ZNmzZp165dMsYUA5JG90FqfPa9aNcdqbKGMq7G0o0xiQ4yT5oBM247/fs5uh3uIcNR1lp973vfS8xIM5mMhoaGyo6PG4/mtyAWCoViwOf20U3+4gKn4eHhumft9I9LtHXAcYWVsbEx7dmzR1u3bi1r/brhhhs0Pj5evNb8GVLjrk3XquwfK79AGTcDrlTZE0Cq7DoYd33Vqkyo9n50fa6io1peEu3u14zo7LSulc2dp//lf/lfKmZrjLYY5HI53XrrrcUx2ZIquvzm8/liwdG54YYbij0P3Ha478U9QiCpm7J/rbtrI25qeL/yJXr/uNawY8eOlbUUGGNi89dqU8hHz4WfbrtKRkmJQX00f25kYqBax9H/3L59+4qPNooOv4jj8tw1a9YUW54GBwerVq75lU+FQkGPPfZYWVAyMzNTrDD0W1hPnTpVtr6kCvWkMZVxDwt3ea07nq5ioJX7Ni4/cS1orqIhKtrlvlAoJFYCRvOPuC6I/vFJ6nXht6q6bY4LuFyFu79/0XF3fktvlFvud1GXVFa5nc1my1qfR0dHKwKsuO2/7rrrihWN0eE7Dz74YLEnTaN5kr/dbv+T1tFM9/luIeibBbWCr6SEK6kg2khm3shnqwUPzXYV9Z/l4rpbbtiwoSwoGxsbS3wQps91zYrOcBXdFr9rU1yLw5EjR2If/eC6fLiAxSUcribn6NGjZevKZDJl/dQbbRmIO15xhc16nj/33ve+t+Z01/7sksaYsgJOIzMTRvk10fv27dPmzZslqdgqEFez6bjfd5NyVONmfHUDyf3Z/qRSS8L69esbfkREtXsw7r6Nu6+ijxDwAyZjjG666aZiYdZvsZeCig03y2m1bkxJ6UG17XAF22PHjiXuv7W2eN3l83nt2rWrrJDrWiHizqWfoTfL3ad+IcT/bVeB4N53y6XgIbovvvhiMU2IBs7+8Yk+UsGdo+gsvY5f6D116lTZOZNKBcZqQXq1ySn8BzRXW49TLS9pV6VT3Hr8wqPrOumnkUnX7cjISPGzUuWY7LjZFt0x9bfDbw133cLz+XxFJV+0AO/Or0vroteX64JdKBT0/ve/X0888UTZNeHGAp09e7b42y5dcecjKV2IO46SagaJSUF9XMub/+xTKf7h4/52VAsUXeubX+Dv6+ur2gPEfe/JJ58szv67d+/eYg8a9/v+ProCus89HsPnn08n+qDyuDKLy+f8gL5aq547p04mkyn23nCi91Kt+9oPrv0ZdN0wkaSKOV+hUNDevXuL3/XzsuiEaf5kUf496I5PdP+vvfZaHT16tOz33D0ed5xc2u93b4xur7uP4r7vumz7s01HWwVnZmaKZbPx8fGaY+3celetWqV3v/vd+s53vqMTJ05UbHczwZ6TyWTKhk7EBX4zMzMNT9zUTQR9s6Ra8FXveKmmaxPOXZBOn5FWLJMWL0z8WFkmNHS1cpcKwXcXL2y6q6jfrcCfSW5kZKRYqJyeno7t9uPzj0VxuuGEZwHlFi3R9l/+mCZOn9Twjet06tSpYmbmEi4XSMUVvKIJqvtcNJHbcsstZdtcPEYNPKPIqShs3v4hTRamNXxjOD1xwjmMfi9u1jF/H6TysXGSGgqOKoTblZ+5rM//+X8ry2Tf97736eTJk1q4cGFsV0dJymayOvz8C3WNYZientZzzz2nffv2aWRkJDbImJqaip36vda+JRUeisfWWm2/7xPKXZv8cPW4Zzw61tqyio24sTqHDh2qen/V7CYeXve7DuzX8eMntGr11Vr31rcUCw7VgrJMJlPsAvqVr3yl4rOrh67Sq0ePVDmCgW9+85t6y5uvV8YYzTTQvVMqFTYy4bXgjqs/NkuqfJyHezyCP6lEUnrpp8NJs/RKlTPgRsfCutrjWuOW4s6ZpLJgpp71VOzDoiXBfffKEU0ce63u8U/15AVx64mO73vttdfKvhM7LnroauWy/dryznfqR+FkGu6xJa7S7fXXX6/4/fHxcR06dKjiESMuYMsYo9HHHi+OpXaVfO44Ov5kRNGJRlzl0LZt2/Twww8rm83qiSeeqGjZiqaviZNRxBzX6HGMjimNq5SoFtRX5M9nLwbL37pe+fNTlUFIeI1MjL8gWavLkTHR0bGRruuhr1YPEL+Ln+8b3/iG+rJ9kqzktRJt37692D0+qZLvyhWDemPqTLGA7X9u7dq1petrxUrlLhe0/a6/H+T14f64yld3zl0l5wc+8IHEMeNue4wx2rx5c3E8adK9VHGPHByXjp3Ujr/6avG4+b0hXJnD7XucuMDUbWd08qTBwcFikGVkZOSVO4aulo4eD65FBRXC58+f19jYWHEfb7rpJr3++utV7/GoQqGgvc+Vd280kq5Zs0bv+8AHNDg4qNHRUf3kJz+JPbfr3/IWDedWaerSJY2OPa3phJ4w4+PjFT2qqnnqqaeqzujdinvuuUeTJ/IaXrFSWrZEo2NPl+XxksrGH88FBH09ICmhbzTQinXugrR7f+n15vU1A7/coiUV34kGUhWZwNHj0msnpKuvlFavKgswMjKykqxscSKW6KycdvJsMcCM24fhRUEC1t/fL1mruzZu1uTFixq+YmWwvZH9zUnK2T7p7EXl1lyr97///WW1wft+9LSeePYZSZUFL6lyWvvh4WHp/EWNPv64bPj5Lf3Ly7Y5t2iJtm9+rybeOFm+XY0WtDJZTf70ZW1as1ZatKTqOWykYqDserJWG65fFxvE1O3cBWlsr2SliaOHZb3jVSgU9P3vf7+Y8cdldNlsVhlJGxdfof3eYwXWrVun559/vuyzg4ODOnXqVDFwj2u1ymQyWrJkScPdVqX4Co89Ey9KKp2TiSeeUu7nfzb4wrG8NJSTVq4ofn/r1q2xzwZy2xbNGJJaoWK7E0XvAYWZ+0QYiC1bIu0d16kTr+up534sSXrxyCta9+Y3Fydb6O/vly0UtO7N1+uFFw9VdH/LZDLF7a9oHX/tqOrJgq21wbolZSTVHpURMFJx/bZQ0MTB8eIxKHYrLBR01//6K8XuwH6gtGnTprL9lGqnl3EVcRVpbliAmph4seIa9sd1Jv1WXBqeWIFVsEHhopYwPcifO6sdux6Xwu5o27YFE2QnVjr56Yi10vBqadXKijQpbptzuZy2/8Nf0+jjj+u58YMq2NLYq1s3bdLQkmUavvFGSd7kIoWCtm+5TYtPna04bs7Qypx++tOflr3vzqvfoutaFbOuG7C16rdZTRwc16a/967YRy3cdttt2rBhgw4dOqRsJqOZsJXadR0cHR3V1nf9PWWMKQZEkyfy2jR8fTHdnfjJ3rKAKXa8tDuu7p7ZuE5auaLqeOf+vr6ya9xXrYK4mD+P7Sv93sQRTVyMBCkHx5W7HKTzw1OXJWvVnwnHRF+/Trlsf7CPoehYb/9cVbuP9v44ufvd9My0suE6p60tbtem1W/SPT/783rof/5t8bN+WvSh627U4MLFmtBlTV04r8d+8mPN2IKyJqOzx09ox86dwb4XrLaPvFe5xUuVu2lY8spN0TzAWKulJlusaFtusvryN/5GVjZIeMLPW2u1e2xMd4VjwYr3wKJlZXl9xT1y+qImJvZJMwVdLsyov69PNwwPa/yllzQTlhdcOvXJ+z6hfc8+q6Mn8zr40k81E7aCuccR2UJBhZgxf5lMJjivlwqamHix2GLYl8novWtv0NIFAxpe/1blXgxa8PLnzmrHnh8U11Ec1jJ0tXTyDY1aW3mPe6367rEFTsYYzRQi4/UkvS93jdZdzkhnL2rryK3BYxQuT6sQyTH27d+v2259n2T7NVoIrsdCoSBrJIU9j1avXq2HH364asB3/dphLVi8qDirtLt+okHz9ddfrxdffDFxPbW8613v0ro110pHJ6UTZ6QTZ7T1LRu0f+8+mUxW04Xg2Btrg2M6RxD0dVoDrWxxtdJJLW91O30m+H+hIBkjHT8pDdco6J8+IylIVJUJv3P4tSCQUr9k+ko1SYsXBv9+IRyDMzklnT5TvAn6+/pk3eBsZYJMyBtfY2cKMkba0BcGmi6gccdtYIG075BykrZv+pkg6FzhBVSZTPA5d0z8/ZWkl45IE0e1/po3aTSTUUZGKhRk8qeLCXT0QaVuQH5Z169FS6T9L+mTm9/rbcPi0u+dPiNNnVdu0RLlFi4ubZfUWEGrry84RsuvCD5/+Ii0aGFpnyL7W5H5RDInnyu4Tfzg6SAo/elr0srKbSlT7fo9cqxYUh9esTKsbyxPrKdnptWfyWrr8A2SpPOXL2lx/wKtfutNmjxxQsPZhcotXKLtW27TRGZaw9e+SVq2pKx2PpPJ6C1veUvZ2KBVg4Oa8FqTMpmM7rnnHg0ODhZrc6XGuq1GKzyGz10sKywNrxiUnjtY+sLrJ6WbbywL/O7+5f9VD//FX0iyZS1dFQ8fP3k6CBxXLJMuXZYuTwf3V+7qUqDvjrtUrMjYvvm9mlgxoOFr3xRk7pHMce+x8ta4vbuf0Z3/8N6y8y5JB39anhlmjZEKVhtvvCkInLJZFWYKuvHKIa0YWKTdRw5XZOJJCpL6TEZXL1uuo2dOV7T4ZYzRlmuGNfbKhAqyCvL80rk0xhSDn7LW6UxWk889r+H1b5VUec1XVJ4tWlKeTvkSruuKNPenQYvW8LmLMjLqMxlZWd198xYNjry92MpWrZBea3rzu+74iCYPHArSlFdOSIODxWsqVpiuTJw6IVmvVfJEPr7SKfK9Yto4cVQ6/FpFRWDsNp+7oNxPX9PW3BrtO3RQhfCUZrNZbelbplzfUumnr2lPf9AqV6woOXVC64fW6PGJQ8VKP783wpa1b9auPbvLCrnZMIjdcP06bbjiSu378bManRiXUdg6ZKR+E85Kujg895cKxQJnsfvj9euUOzWl7Zveo33HXtPoxEHZsPWo2NXzyPHSPW6l4TcuSBfDvCxjNHxRUlhA1UwhvnB3+kxwH7p92DsujWyoOI5SOKY0kw3S+NMXS2l13PWYlPa68+hYaXg6I4UVZ1KQHutEsF25xUuD62LyDQ2/7Sblfnq0lLdv3lDsyWMU3LcFW9DGq67VlTe+Wevf+Y74a/vcBen4SW3MLlI07HOF775MJsgO3PmyVsOnzksXj2idsvr0rbdpYsVCDV/7Jp2aeFl7n3tOG4fWaN3gquA6lJS3fRo1RhkTpMHm9ZPB9RWmBxOnTyq3eGlQ/hhYIK1cUezy++j3v1+8rqyVhs9eVu7UVJDGvnFGn9yytZiX7z9+VI+9dFAz1spYafLlV4Nzd3Bcw6cvKnfijHSiVD4pqwRfsVK5E5PF+6o/k5UKViNLcnrRTCjj8o/h4eJ9dNuyIeUzi3TopZeK729Zs1ZbRhZq37GjGp0YD4tgBWWyWRk3C+/pi9L4y0HeJKk/G1y3G1atDo5DGOBL0sQbealQ0OVwBvDJyUlteuv6YoXB9k0/o4nJUxr+mXcV08rcimXKhRPhRCu+g/TPaNqWAqusyWjy0gXpWHBechmj7e/7oPYdGtfj4fEsft8YTbyR16bVa7V9pFSOkhT8e8smTZw+WVH5kJEp5j0ZY3THmuulDcFwiGLvkLDnRcYEDQx33323BgcH9fk/+bwKM9MVlY+VJZXINSxpy41vrUgzc8dOa/vmoBy6fMFCTV66oOHBXFCJMkeYRmZY61UjIyM2bmxA1zXYytaR9Zy7UF4r6CX0iU6eLi/cXjMkHT1RChyl0v83r5f2H5KmIpOxZIzyb16tiVdeDhIqKSiM/MytQevSuQvKjz6tiVN5Da8YDBIst31XDkon3ghe26CNsHiHGlPaF7cNw6uDlo6Ll4pBYlkmHMqfPxtsQ5jQ7Bh7QmGJU9vu/GVNXryQPAB/4kgQQEZdtyYoOEV/z6gUXB9+rVTQcts9UnkO8q8c0cTfPa/hQla5RUuD9WVMMeMM/yNtuCHY17AwkM/nw8zpQvA9o+RzfPS4NP5yKYBc9yZp9arS+35B48LFoADjfjt63T17QHqjVADJnzurXUcmNPbqhGRMUIOZycjIFGtky7hz6e9j+P/8m1dr34HnZS5c0vp3vF2S9Pn/9l+DWlsZffKDd0hvnNG+40dlJK3fuFG5TTcH2+HNCNZwt9XI8cmvWKiJ/QfKr1HfVSult15fej1xRPn9LxQzhSN9BZnBFcF2hN2tJJUqSeKE12TxfK+9unQNGSOtGgzut+g9J2k8f0xfem5X8fW9P/N+rXvPu4LKg+OngsKeMRrPTuvh//m3wS9Y6bbr1mn90GrlFi8L7pNTQZeW3OKlQY3xWPA8QCurO27cKBkVM73lCxbqyNnTOn/5ksaOHA6Df2nbhk36yr49wXgQGz6aInxv+0jQtdjP+PcdPxqcs6E1ym29tXht7/j85+WiDHcd5c+f1cSSfg1PTZfOi39PVUsz601Po9fCwowmXnxJw8uvUG7p8sp7pwFl6cvx00EFghO9pqISWvq2//LHgsJptXvbtUgV84OYz8XxjkX+wjntm56SWTig9ZezpeDSSPkrFmvHN78evA5b+nILFyvfZzVx5rSGN64v9S44d0HatVfj+WN6eO/u4JK30m3X3Rhci0uWFlth8ufOVhYSw+tTmdK9kl+zUhOHJzS8dli5V/NlaXL+3Fntu3xWo889GxQsC1bbN/9MuL5TGh5eq9ylyvKQ/9u5G6+X1q2tPB/RPHbd2thjmv+7g5r4yb7SNbQ2DCIPHy3ugzaHQXHSNRrNn/3t7CtoeNM7KlsDw/OjlSuk/OnSsmuGgm09eVr5p54p7eeSZdKN8fsQvY7G88e0+8iEVixaonU3b9Bkn9HygYWafC5IN4Pj650vX26FdGqyrLUtdr+8c79jzw/C31Z5vuLlq0G6sUN2ZiaopNk4onW5odj1u9/YMeZ1vR15r3LvuiWomHPpprtXViwrPzdrry6WDYJtPVXML/LnzgbB9ts3KPe2G4NyxESpsq7s2vKOTdk+33Rd8O9Fy8ru7/yVyzTx2hENX7Cl7+ZK57dsn4y0/df+URCcHDxcXoYaXh3kL87moLvw5//kT4pdMPsyGd21YbMmL12UrhnSI4/+zyCbSsrbVV4eMMZU/WzxO4OLteMbXy+etztu3Kid4/uLec/dG0e0btXV0ro3KT9zWfu+Pyojq/VXXi0ZUzqWb7tRWrakeE3LSt86GPRiyRijuzZs1pGzp3Xy3JTOXLogW7B66fTJ8JAY3eOul5uGy49XnITyXDcZY3Zba0di3yPo66B6CtjHw8x+QX9QIBzKSQsHymv4ktZTZyuixg9Lr4bd4erJ5P0AJ5oohDWtxURw7dVS/g3pzLnK9Vy3Jgh84rbT36c4SVUx0eXRINCYICg6MxXsR5XLuyzBXbqsPFCKbnNS0Ld8iXT2fOV+uG3xj1fcsXGiXa9WLg8yw7CQrjWrpCWLgqB273jpexvXBQHg1PnSOXbrX7UyvvZ4bF/l970WpeI2+MF2xkhrVwfXqVvf371YrOHz9zt//qwmFvdp+YlJTV48H5/Z+8dpaFDq6yvf/qGVQWbrjt/QSuV/eji58CCVtbpVqPdeiQsI/OA3eh6vGZLWDJVq6198ubxQNbQyOM/HT4ZdMU31DMQpBsThPTZR2aqXZDx/THuPHQlqzd++MaiwiamUyC/q08ShF8uPp6tIcZ9duEC6cCmxcBLd3ujnqhbW4+RWSNe/qXzc6k/2a2L/85XfW7KoPPD17ym/cBVN8/y0x11/a9fEtwb618KGG4IKJafZSryoaCG+2nXsb1s4lrbY2hjTLV9S+XXv8hwXZLjeB8uWSK/ng+N5zVDpWEV6XJSt+/SZygJRxii/JlcKvGym/L42km4MW7y9NKvi+nIVTdFr3khaHDnvxcoir4Ug6V7JrVB+Ub8mdj1TWZFz1cry4DvOFUuDPDqajpw8Xb2CzImm827b/SB87dXS+Qvlwcbaq4O0152HpHzTT/enzkthS2ZwnGKOZ26FtPFG6dnnpTfKu+Fqy8bya0YqrTsu745WKLvrulazSoPyg4s1ce6Mhk+dLz9/frBdrFQ+UT298dcbl8a5bXcVC5vXh2l5lfQ4moZKQfCwYlllIF6P69aUn/tIN+KyoTUrlkm794XH2yp/fiqowBu8Urm3vy14f1dkCMIVy6TJsxWBbf6Z57Tv0HhQqepaEsMgKD91pnZaHio7rrmcdP5i/Z+P5CHF37r5xqDcklSGjLnWa+Vhse/nVgRpY1zZz3EVJz2EoK9batU2JyUALmBw35EqCx9npiprB5MymUZa+qKfN5JGNgb/Pn5SujwdJDIuQ45mWr5qN0M08/P/72QylTf0Fcuk02eTE04/4XfdTuMyuyhjSjWbcRn4hYuxtau6aTgIqgve8XWtVi5gW7lcmimUtYpVBH3RwD5a0DcKMuczU+UJkLtWosfJtc46frdZL1Oo2qJUcT68z657U2Vr1TVDwXFaOCD195W3cC5bXFkx4K6d3Aopm60MIBsVV+MWLeT6x8K973ejdAVc12rsB8R+C+iRY0FQ7re+JrQw13X9lX1e5efFFTSSMp4rlklvulraezChoqSB33e/7T5+49rqlTPtFpc+hS1CNV0zFFx3l6fLuh6XrfPcheC9aGHYJBTUo5UFSZUH9VYqJHHdfb1xojXXm9Ql0BXQly1JDlL9+yIu/XaF1Gi+c/J0cP2vGQru8937K3sx+FYsLU/3ip9T7UDApTfWBpVe/X1B0BGtWHGfdWlatfXGFcjd8jWrygPU2O+rdG9Gg2r/39W6aLplly6Xp5HFXjQq5Seu+dPdk7Xu45tvLJ3zpApHnzvP0ftraKX0tuvjyw8b1pX/hn9uoveEy2ui272gP9j/Zrj7fNmS4Ho8crwy2PaHnFRbT63zHa5WQyuDiiGpeuBmTKki9dLl8jR70YB04VJ4Xow0uDzY/pq/710X69YGFS1uf12vn7i8Kq6iJqkcI5XuN6/lsszQyiCvOTjRfBA/0C9dbPK8Ry1bEpSHOslV2lbLf+qppJtl1YI+xvR10uKFpRrRWv3yfa7g6MZvrV5VWo8UtvRYlRXcDx+Jr60+fcZrcQpba6oFfIePqOyOtioV5IutfZKGXbeU1yRbKAU3fmZ89HhwM8QVnBcvDBIsV9A5eboyAV57dVCA85eHXZmSj52C9Z88XUoc/eA0iQm/d+5CcHytd3xdzV5UxgQJq7/e1WGL3MHD4fZY6eRk6fMuIFwVmbDBHR+3f+59l/haBdu1JqaFNlrosrbUSua6T7pxgKfPBBvgzplV8G//uGYype+5fVuzqryLb1yGGq3R91s741qC3brdNdNqjbANz9WyJaXxcuMve4GYd08VA+BIrXs0iHM2ry9vHe8LxmEUg/Rj+fiAz607amhlULt64VL58iWLpOuvDf7t7o3FC4N9SrJkUXB/Jh27RgLOpUuk1VeW7p3xl+MD/E6xKh+j6wcx1RiVB3q+weWldcUV2Ny593/XiY4VXrywdotgMy2ACweC63XhQOV6ozX7tX7T727utxj7+7d4YVDwdmlB1GtehZG7xl/Plypm8qeDwo6rkEgKHuMCPqn2fe6CkWhAJUm5KyqDvoINewfUuFaS7gVrg3wuKQ1askg6d760j8ZKB1+STk+VBxxx3Wkdd47c37kLwbly6e3w6sr8LqlC1JfJSKuuCPJ/fwxSJhPcy9UCm2Mng+AkWjF0VdglPmb8oC5eqizXuEBWitwzXl7j70ezAZ9U2h9XEbpmKDjv5y4E52TJ4iAorOXI8SCISbpGi0ypbHX0ePVKNP8effb58veiLVzXDAV/E0eC/LHatSkFxz7/hlfJa8sDOL810l2H7v50juWTd3PVYHA+k9L6YyeD49pKHt2ugE/qfMAnSdPhmMZrhoL8xR+D4vKNM1M9F/RVQ9DXaXGFBKmUkSVxCculy+UTcyQVWo6fko6/UVngcL/jEt2kwmNZP/3Ie88dDLq++MGo6+bnMi0p6Ja1bEmphcoqPlGSygvVbrvfOFPebefydGXiXa1mzChIdKXyVo9iYT5ccMXSYMIZVwO6fElQm+MS9ejxPX8h/vesDbvseZ9/9VgYLNnyz8V1j/TFVRCsWlle4+bXtrqANHqyXO2hn6kWwuto4khwnt32FGuTw3WvWlneJVQq//fREw20GoX7e/5CkFnU85UVSyu7GDXq3IXSMXv9ZPn2untgYEFwnt0xKsQEwC5zdIWn4ycru9i49RYKwWQ79QZXGRMUNs5fqAz6zl8or9R5/WTYmvxy8vqOHg/uk6Rzc9VK6dip+rbvzFTwF455UsYEBY3ZYm3peosGPVW/p2LSUuHUZLAeN34q6ft+mhzt1ujOt9+d133OVZS57lFxwWOcst8YD3sGKCjIrlwRXHN+hc5zB8u770mVkztFv+Pudakyz/HzhugxXjQQbJdUCkqiLfHH8sHYw2VLgjQ07t51Y7STWvH91tnL00E+ZhRUOrhJr6TKMVRxwVmrPQWigaTvirBC0P2oVWl/rYIgMDpJ2vGTlRW4Fy6Wt+hG0/yJI2rY6isre9TUqhx13jjjVQyHy4wJrvnN6yuvGaPguogGfHHBrV+R6Srd2smVL26+sTyfrDcPsTY54PNbrDeuK93PSfeMf99KwTGpth1GpWP8ljcHxy+ux05U+GzSWC69jqY/rkLm8NEgT06yaGHte6ieltF6JbW695KTp6U3XI8eU+oKvzcs17rjGjM5X68i6OuWxQuDxCTa593dCGvC7omHXyvNsBbXOugGQifd8FKQKbguEC6hiWsRlJJvwLKxDraU4LvtGlgQ1IRMnQvvj5iumYUw4TcKu0R677/4cuXEFEdiArAkV3ndL158uTx/sQqmY5IJu2rkggLGVBjMTU4Fha7NG+KD8emZhBac8Lu+pJpiq9oJQ1wFwRWRQKi/L+hek9RCmlT7Fe2uEXt8YrbB//eGG5K7hkRZGySW4ax4dXGFzFZEa5BdgcsfuxTt/uQXSlzG2xc+Y8q954+BiutCNnGkvoDYGOmK5fG1qUbxXbFemCgV3ONXWv03h3JBYbre8YSSV7tcCLomz6YLF71WaTWwzd6/jYICmJ82xnEVQn7BrqLruXe+Xz0WpHPDa0rXUrR7Xq0KvehvlAVpCoL+jeviexe4GTc33BC8doV710sh+h2joCLIr+zzW0/97mGv54P048KloCLu+BtBK+/pM5VjbqVS+pOUJrjjsXhhfFd9KThH0W6i7li7fXXBugtwpSB/iWuh7JTL09ULqdHCnzsX/n30xplSodqf+ddPY6MVffX0fljjTVDi8mQ3FCOaP8XyKui8yZ6KgZ1rgXRdKuPGdkqlyjO/15Ef1Fbrot6KTqzzxjCILlZ4Hi917V++WJIJWpZdfhPN22u1OPszoy/oD+6z/BvSpenqLVgzM8ndL+Mqd46fLOUpVsE9npRPHT5avStwO121Mkg/6i1PdJNfGSwFaV5Z+cnWX9HXAwj6OqnWOA93c1upOGGKa03wWxpcQjqUq6yBchlm3A0fna3NKjkwrFbrG7V6VXk3Iamyz/M1q4IgLq4mzaqyq0NsLWudCVBuRSng270vPuFytegFxRe4CzYozMV1C8ldERznWrVcZS1wUQ0mptFWDlc49TPd428E3Y58l5MfwF1VwQbBcmQSjbJruJ7xB75GWu2MgtaoVkVbZa/zat6jLSRuXMWyJeFxHS9dO0ePB//OLQ/OvevamiTxvHvcvZV0HKt9PSkzdq20y5YE6Ue0MGBM8HvNZuZWdXR/arNj+aAw3Eia5PMrgPy00bVk+5Nn5d8Izq/frTJ6jUR/2soLrrw3rS0PHquJPj4hKqkbljsOZ6YqW4mOHo/5vIK09eRkEEBFu+r64x3dpBD+JDd+N3XfdWuCzz//YpWdtJI1QZqUtJ9npoKgMy6Ac7/5xmSpgsba4Ly5isxaY/ja5djJ8rFkbghAGS9v9YdVuPeirShHjpXNwiwpCCqiXJYfrRj2H/8TnXW5oUAoXPFQLshTZIPzdelyZQteXAtz9D51vY78WaalsKW0AzrRzW/8cHBfSPGVM1LQPX9DOH7Pd/J0fce/UGhogi5JQSVWXFnpmiFpero0HMBdD9FjXm0SldkK+KSgVTF63HqVK3sVCvHn1ao9FdazhKCvU/xBzEbxkxNEu+4tW1IK4opjMpSckLr1RfttO3E15bYQf4G6MXZHjlXv5iIFBQO/i1NcC+SFi+GYkSa4ALjejOvkpHRqf1AQqJZw1UrTkoK6FyZqNqZo5QqpPxskumemKhNzU6XbV1zlgH/u/BkGo4XFuAxvQV9QY9io/OkgU/EnvfAz/aWLkr/bKtfauGYoyEzjxgDWIzpmYHKqFLT4LSSugHJqUjp1Jrh2/OvDXUcnJ9vX/WTpYunsVHsLqe64JdWYWtveLjmzYSgcT+S3WriW1nonlPHTRtcTodhysaZyfN/R46UCnN+tUQpq/aMVRcXxct6yjKm/ILNiWfJ1ZcL3k2aSdC3Pq1aWjyGr1sLo8pOK/VD5s0ajXTprBVVDuSrbGf6n2vXnupwl/Ya1kcqjmH3IZILKr06P8TkSjufavD6YMMqf2MyG2zqwILi2Ll1WsedA0s6dnAz+/PJBNNgva70O17VmVfC7+TeCtG1oZan7d6MTLi1bEvTOceP1/TGAL3m9F1yAN7Cg9BuFsCzh7tOyx8KocmjHbAYVrSrY8jw47l4t2HDCt7BwUGuilDiN5i1Jx9BVUr5+MvkxUo3q5Dmr1dW0l6xeFVYwVTFXAlgR9HVOtFk92t8/WhNowgKDu3hcoWLZ4iAzc10jj+XjJ2xxibb/sN0VyyozAatSV8ZoEOp326jFD2DiChvu2TuNMirNGFgvVziJqyVtl1r7cvJ0kEgeOxVkynFdduOOU/QRCv7sk6623Zjyc14rIW8m4HMKttQ9J9riUVdXoQT1zNZWsKUCVLtEW9WOHAsKNhcueo/EUGXB1J2/do43ODNVu/KgUWaOFaZquWaofFC8G9vqRCe6iOOCRvd9KbnFwinY8q72QyvLf/u6NaVWdDd7sRSkVf5senHjApPG8CbNFukKQ9W69hVsZZ6yeGFjlWVS8ANT54OWDX+89Zmp0iyocVzQuXAgOFZxY4HqaaEt2Na75xUKQWVKp7k82Z3TBf2lbrOu1fG5g6UeH8VKW6nsRF6xLJjF0AXLfvmgahAd/n70mmmlJf6sG79biF+3PyY0+rggKRjb5MayrV1T6q0RPe+dTKPq6QLbjKnzQUBc7Rr2x2wmTfg2G/zj6wfr9Yq7hzt5zqwa7znULdN1lKdo6UMFVyPoCgDRAMDaoOZu2RIvoTXBs1f8wvaxU5UTtlTrUx83O1XBBmOQ3nZ9adnpM5KbjKCW6GcWLwye6XPkWFCY7svWP3FEBVN9ZtMkVvGzus0md1yKs4uFuZG15bNu+oVBN9jfcbNPutpsNxbN7047vLrxbiGN8FuVpfLZPJvNCOqdra3dgVaUf31kTHzm6Ar8NZ7z2BR/fdHxmk2tr80b2M4ptZvR31c+cZVfKeImUqmnkOentdW6pEW59R47GVwfC/pLXRyNgtZAqfTYAtcNNW5a/mozbx4/GR9QGeMFuTV29MxU+bGqt1tZVLGgHxZez0yVz9Qcx3WHrxaAr1kVdCebjcLdbNV7uMnVxvYpsRXUTyPj3r9iWXKrpAuiz0wFY8mj3fXbfb+79NafqTlq+dLg2Ypx+bJVEOgOrQxndpzlCij3iISXX2t/N/RGekgUCuFYrx6pgGt0O1qdBKlRrgJjLqj17E5pTs3gWecUT2jYqpXlF7UbK7F7fymjHtkQ1CAPhZl8Psy03fg7N4g++tDZQqG8O2dcn/rd+8OZhxISwmMnyzPjgQWNFegPHg7249yFoHB8/GRQCLr+TeUBn1HQra1e1gb9vaX6ZyDz3TRc/vqaofjPzQbrFQqOHC+dk117g6Bu1974mUGjXXxeOlLeN99dW80cn2pcbZW7Di5eCgK/VVeEA9tN6VocWln9MQLNms1Ms5DQ/WVmJti3TmdKrQZ8nbCkgXu1Ew4fLaWRUvkMiFLYomKq39fPHQyeJbVrb9CCFe2u6YIzl/7mVsS3wBZscJ+633etga+GXeD3jQf3c9IjeYpjqW3QQuLSy937w0qbmN9cNVgqXI9sKOUNcU6eDoIPl44njQO8Ymnl/hUnJYl+2FtQq6tgtULxdWuCcbAu/1k0kPzZbmh6e2x5Ht2Ml46UP6bGBfquguPYySBYbnZ8djMKNrj24mQzpYrqpPT52MnudCO3Ngj4omPbu6GVnjCdUC3t6AWnezD/mwdo6euUxQvLx4K47pn+9NqLFwZdOvbG9AG3NnkQvVQ5Tezaq4PaBjdpg1FQCKjWOnMsH9QsugfFNsLayoccu37a/nMBVw02Xov00pFSoa6/LwiM6qlteeNM5djGXhnP5I7RCy+VL3/9ZKlrmFEQbEQze2NKragLB4Lg2nVRmzrfvn0s65cebq97SL2byc9dz+6czrWxGvXInw7+eqUmMqn7XCd0u8tNdBbiaIuIu4+mzgUFveiMv8XPhf93s21uvLFyLLRLf89daG6/3ZgeqXLcdrSAbFTeUpJUeD5xSjrxRqmFP5ouLxoIfqM4g1wYiF4zFN/LwSiYLTab9QINE4wRjpuR06rU26QVJ0+r2HPEmKAWvNNpcSPd/KpNaNHK+v28r55juGKZ9KarS3lwN1uKktKYvmypEia3oru9aeK8cWZ2Jpty+XSvtOZVkzHtH0owGxrtltorOlEB3iEEfZ1y7kIpaCtjK8d9JCWi1S5+f6Bx7NTfNsjU/QJ5tPC4aGH1bipR0QJ+NBMv2FLA4roE1vNg5Tj+A1jrTQNmu4tCvfypvuO6zrnC26qVQetBNLWOTsZx5FgQ+F2e7tw+L1kUtJaEdRXKKL57zxXLux8oRF0zFDNGr4nMpJHCWydNnu2N7ZgN0fGv0ecYOo20kloFrQE3Dpe3xh09HjyEfOWK5lttilPyq3KMXTTtcvuUdB6vWBY+PzRMx+O6aq5cEfxF84ykgMrGrSfsTRE30ZYbW5403rBefqtHq5MJuef41dLp26Oe9a8MA+zjp8pnc078ri2NpW90EpbZcuxU5TNP5xt3Ljs1frCd3ARTfXOweD9Xr6851L1zDl4Vc0TSuLRoq0jF1M4NcDPSSd704lWCsuOnwhrhN4Lxb42OC6unRccFJO7RBxNH1VIqOZfSgBVLK7ssuDEHx/K1H1JeDOBq7LRV52vNo7NnFqx0NqZV5Y3Jzm5HM+KOzcrw0QxnphqrqXaz6nZ6ZsBqkgKfNFqxtDw4u2Yo/hErjXrjTFA55sZCjx8uXSft6pblj7E7HrnX/cfcJI3JfeNM9dZlo6BnxavH6g+E4liVZveLe3NgQdA1E42Lpi03DgcteOfCZ+BFj/nlmd4N9pxixcZcyozbbHB5MHSl0dk5u8GN0eyVXk7zQaceR9IBBH2dsmJZcq2QXyM8sKC5xDRjSjOs1TvJhl/j2qkEwQ9IVq6YXxlF3L7euLb0AOJjpzTrUWzcRD7NiutKN1e6dp483Xy3pG4GfPON66Ltnlea1H0zSW5F8mM2rA0muVqxrDPp36nJUmBZTbXuk3GVDMVA0Ja+18p4L6P4QMMoCE79B85X0+yjYRo1m2Pb2skqnNk1PH9xj/5o9PpGd5yaDAK+pHGzvWaOZMup0ejwqC4i6OukWgXicxfC7nwNcl0N/NkFrYKHEvvPyZnNGz/u93qt21+7RVv24loM3jhTqulduqi8Be2aoaAbZTtaMpLM9oO1e1W1e8GYoCWwOE4KXdXMlOPO2SpTrFtb6qrWbu7RGW484qqV5d0qjx4PKn/OTIXPHKwia8or8ZYtDr7b6qMNqm17se+a6j/usxHwxZkLXeykcJIWlQLoiQ6dv14yV85No9wkTnPFfKps7wW9MJFQnZi9s1OiY9ncLF0ZU5qS23+WX72uWxPUxi5cUJm4usKMe7bbbM5cOR/TmHpmnzp2MiisHTtZ2WXyyHGCsnZa2MSzclwt/LIlQVcs9IZmCy21HjeR+ED0Fmc9KD6TzZYmi7luTfksmXvHg26dtdL8BQukK72ZFCen2hvwRR9XsWpQxYmkXj3W2wXGa4Yamw26W65aGUwe5J/rbj4KZbb08KUDdMwcGc8n0dLXOdEuKatWBl3tXIZ79Hhz3VbOXag+eYf/QPgky5eE3Q17dOKT+cI9mxHt0czYt75s8PDVTjyTD73JzV7pt/g1G+j4LZJWkrFBNzD3YPfi8+4amBToxKnOdpu+GLlPZmZKD+judXNhnJKb7Xgo1+0tATAbomlqD6Olr1P6+ypfrw4f0L17f/DMvmYysEYCtaT1D6+RrupQhhTdb1Q3MwcKWml2ebo0QynSzfW22LhOWrsmmGG4lRa+69YEXbx9rkXPDexffWXpt93Y61o6PU42+riC3BW93bo317gZO19+rdtbAmA2MKYPFc/tOBIGYFPnVfaw4Xaq9twq38nTQetGJ8zVQfcA0umqlUEPi9NngtYX1xVn8/ogXW629ejchfju2e4ZpkePlwdwxgSzAPbac84OHiboa7eClabmzox+AFpw9Hj543p6GEFfp0QnMZmNafbdAzlr5d+vHpubD+5Ec9I6uB6ox4VL0rHDpW53694UBICLFraWJlfrdRH3nMhWxw12CgFfZ1yus/a/3spaAL1pDiWhBH2dcO5CeaZ/eUK69GMpMyQVjkkL3in1D8e/F/2Me9//TpKz3kQhlyekqb+Qpo9KS/5XadG7a29L3PZefFK6uDcoMC3YKC35leAz5/9H8P9FP1d7uyTp/JPS+e8EN8elXVLmKimbi9+2Be8MXtc6Zv7nqu3HgndKF38snftrafEvSUt/KXjv/P+Qpg9LhanSdvjfmT4SbPOCW0qB04VRKbNUyiyXMlfUt//Rc+heW0mXnpEWfSg8Rt8J/r3o3dLZvy7f3lrHJ+66ced/4XulQjjVdCYX7EPfGmng3aXv+McxekzduVv0oeB77rhNHw8Oip2Ulnws+N65v5b6N0ozR0q/cfnvgvf63xb8u/BG6dhkrgiWu324/HfSpf3SzGvBOpf+UvD7Z74o6UJwDfrrdMc/7hgnXaP1Xj/VzmPc8XLbX3gj2K+4Y+2fp+kjwTnKhF0E3XXYt6b8/ps+GhyjmcOlcxDdZneOFtxSOtdxx1uSCpPBuetbVbqO/XPgX0dn/1qa+orUf2Pw2/55ctfAghvi0wX3uvBG8JuFKSm7Wrq8Vxp4r2TfkC4dKn0/7v5292B0v/11u33y72Ofm3DJdbt7YSL5+qj3ukn6vH8t+MdxZficr70NzAAYvd7O/Dfp8njpvkjaJnfOsquDYxaXTrntdtfqop9LPtZuuVleOnd9ucr0zL/+Hf+3o59z5+T8t6XMsiCtMyodOz99dOmOv73uWEfv3ehxm/qL4DrLLJJkgvTQKD59W/Tuytf+Ov3z6v9+NH+pdU799UwlpDt+PuHSkb4bSsfEzyei50SKT7cLbwTnc/qw1LdWWrC+dH7OPxkcq2jeEHeM4o519By44+7ub3eMBsLjH5cu+PnzpR9L50alSz8MjteyT5TStrh71l0bLi2L5gXuuky6H6L56cUng+3300l33U39RVAuyiySln68/DqpJz2Iuxf8NDP6/Wi+7n570c+X3zP+eVi4IKjwit4P0WMRTfvd/6fz0sUnql/T0bKMKyu57/ZvDNIsY0rbGrcvrnzp8vboufKP4/nvBGWEBeuD69HPc/10zCwPzqEkmQXB+303BNdZtIzi9jtp3U5Sme+KyORYPczYFNTyjYyM2LGxsW5vRsnR40GXmUsvBRf11FcV3BUzkvqDf/sFfRlJlxUMsfTHeF0h6YyKQy+X/rp0cUzSRWnBhvKCVvQmPvnPw3WGFv1C8JunfluyM5IuSRoI3lv2j4LvuAt+5uXwS0ldNSNNR31vCQoiLvHxC/mFY0HCee6hKgesP0xoXvXWn/WOS19wXAa2BgXk898Ofz8TvmeD95d8TDJXSOf+JvheIa/gmEcs/AXpwiOqrJ5ZJsmNd4kOzI2eG2/bB94TBCkLfzYoyLpA+8orpIn/Kl38YfhbWWnF/0s6/e/D1wnHt3+LdHmX99NDwbG8+KPIZBAFlZ1jdyyyb5JmXopfdyx3HN06Myoe0wXvlS495n22U82GScd3qaQas6T23SxN75OUlUyfNPjvI9d/f3DvXPgfQeGieD6k0oC+rLTs14N/uszq0l5p+mVJM1LfddL0fu87meA7RdOKvdbKtPPYuTRhexAMnv9WG9YZmbpfSxWkP7Nk8T3SwndLJ/93xd8b7hqt0YV80S8EBcRopY1fgC37jay08o/CAshj5esaeJ+0ZDiYeXHqLxVcowVp6W8E6zzzgMquMyn8zEzpde4Ppa2/Hkzu8uPnpRP7ygtuCzaXAnpX8XT+f0hn/mu4rpj9zd4kLbgxzD/CbcpeJ9nLXjrq65eGHioVto7dq1JaJ1VemxmVhvxXOd4D7wvvJ7fPcUxY+DuQvD9x3ynbnn6Vp3VZ7zMz0sD7gzTy7Jcl1TvuPRPkKWXn/ApJb3g/e3MQHPnHWQvC3y6Uft/f1uxNQTq98GfDAnBYsdj/Nuns/9f7fF+wnkU/H7zvglFX+Dz/7fB3Eo5rNJ9w+m6WCmekwkv1H4fsOmnmhcrlkrT4rvL8e+B9QWG5MCmd31naPlcOmD4kTT2sptM6s1Kyp1U9Pc0GwWPhvHR5TJV5R5g2962Xpp+L+xFpxe9I2SHp9H+O2fckCflU382SWSRd3u1td1+4HS6fzgS/O/DeII+pK79w15nC8707/veLwrTMBaH535Mu1JM39Knqfdl3k4Ly4kXJXpJm3lCwT+fU2Hk2kvqlFb8lnf6/VH1feljmWqn/hlKlyabbe2oGT2PMbmvtSOx7BH0dcO6C9KNvS6/do/KMtd2y4V80QHEJTfTcuow8enNnVTsBahZ9CzGbjNR3ozRdbyaOdIoWYvolZaTV/0A6+t/UmfQuoUBo+qWb/5W09mPSj78mvfI7yasw10j2VXUk3Rx4n7TinwSF3IuPtnfdAHpEGPid+WJ8pQDarF961+PSDX+v2xtSVC3oo3tnJyxeKF39uvRapwIpZ0bxNSVJv+tqKkOmT7L1tFC0goAPs8kS8EGVFVthK9HRBzr4mwlpnb0s/eT3pJ98ro5VuFa6DqSbFx+Tjv8w2B4AKTUjnfxn6my5DiWXpdPfkdQ7QV81PLKhU679Wc1OwNPsb2Slofe3c0MAYP7KLq3yZo/MakzAB8wDBHyz6tQT3d6CuhH0dcrym6RrPtrtrahiRnr9e93eCABIh5lZHP8IAOgNJ3d3ewvqRtDXKc/9W+nVr3d7KwAAAADMcwR9nXLwv3R7CwAAAAB0yoLBbm9B3Qj6OiW7qNtbAAAAAKBTrv9H3d6CuhH0dcrS67u9BQCAMtnaHwEAoF6Lr+72FtSNoK9TmBkTAHoMs9oBANpoDj2ZjKCvU0710MPiAQAAALTX8dFub0HdCPoAAAAAoFHD93R7C+pG0Ncpk893ewsAAAAAdMrSN3d7C+pG0Ncp518vf53U57fevsDVPmcj/27HOpsxh/o1z4pGjsdsHbtunvNO7GMz62zHdvTqtd6r21VLN65LG/l/p3+vmXXNpfPZjW1tJL9r5281+ptx342uo9Y6e/1aSFN5otl7sJV7dzb2t9FrrpO/3ej71T4Tt7zVfWtknXTvhDKD5ReISfhc0vJGPmci/45+NulCrfe369Xu9fWyehKUes9D3Gcb+Z1GtOMc1XNdu8/FfbadgWI9+xMtZLV6DGwd62gk86+3QqeedfTqPdiO89iIuPVFt8FE/t8qq8prvtY2xDHeeurZj3q2qd7PNrLeqHakYY2md3H5XTvWW+u3Gr1m4r4bXUcn84DZKNynqTzh51WNbEe0LNbIcW/n/ibd93HXXCcrG/ztSPqtanlXNE2tpxxd7TeqpYfRPDvut+LKdFbSa68lrLT3EPR1wgsvSF//ael1M7UT7aipTrpRer3GsBGtFiiSal9r1fLUU+hPKmTW0mqg1Iq4msBmg6akAlkzmWhSYl1PobaeglojtXr1bH8086/3s3GqnRP3up4Ms9p64z5X616op+WjWs1yM7XOjdboNlOgaWa7TOQvbp31VAT491i7KifaUbHor7PWZ5tN9/zPNnoOal3L7Q4g6r134pY1k5Y3Gnz432v2u3HrqfWZepZ3I4ht9PpxGqnUjFtfNwLXVgLVZt6vtR31rj/u/qiWptZan7+upDKAn4/VW9kWd33s/VoDG9hdfd3egFQaHZW+Z6WfU/BYqIw6F/gVVL22ptHlc1G3Ar9mf6/Z73Ur8POXdeu68RPl6PJ2/kY9y7rB346CKtOUuO2ckfSGpFzC+/73ko5vUvrir7tWGjStIB10/+9m4Ffvdztxnb0i6SoFx6qvyjqbPQatfK4R7dy+RtbRaNDR6Xu31r3TicCvme802uLUyjakMfBrdr3dzDsuServ8jYo4ffrSavbsd3TSk5n/WVTkhYpyNNcM1jS41yTtu/AlU1u5Owj6OuErVul1yT9S0lvkZSXdL2kpd5nziooNL1P0kpJZyQ9H/7/FknPSFom6U2Sziu4KE8quEDd919UUOhy639r+PljkibDddwWvve6pHMKEoMnJV0r6YZwXafD9bvf6Zd0TfjejIJCnfvdJeH/pyUNhL+9INy2AUmLJS2UdEHS5fDvtXC968L3MwoKQIskDUq6KOmApOWS1obbfkzS6nCd7irtCz97XNIJBZnZcUmbwt9UuO0Lwu29EB7jIQU38QFJq8J1LJV0KPzc5vDYG+//10i6Ndy/S5JeDrf5lvA4SsF5s+H6M+H+TIXb9K1wGz8aHucj4esrJa0JXyv898lwexaH23hA0rvD/Tgd2c8F4fb3KbhWzoa/byPLrg2P3Uy4XdPeeToTbnt/uK5suJ9G0tOS3haeq5OS/nv42fcruJ6uVnBNXw6Pw8XwPEnS0XAd58P9XBZu14Ckw+G/3Xjny+GxOhcuvyo8hsvCfZ4OP/dTSS+F26XweL4l/N7zkv5nuPxnw3OzUsH1mldwft8U/l1ScF256/tMuI5FCq6dn4TfvULBNX5J0mPh9rw1PDfHvP1bodK1Ph0uPxy+557T+lq4j0vCZf3evr/mbZt7dNyR8D33uSkF19GbJX043K+fSPpGeHx/TsF1cSbc/4Xh6wXhvn8j/J3bJN0RbsfScN9eCY/7DeG//0t4bN8l6ZSCe+fp8JjZ8NgOhMfIX7e7HlwadFX4mZMK0hw/jfLTKoXvue8sVnB9XRsek34F19VM+LuXwn1398aS8DNG0g/C/y9V+f31UrjtPxMeyx9Leme4fS5t2B9uw7nwMy5ddvf56946XDowKGlYpWv7tIJrY2X4u+fDf7v7YIGkRyQ97h0vq/K030/P3h7+lksv3DqOK7jWnlZwTbwl/JzC9S0N//9KeN7curLhdkrB/WrCfbwi3McTKk//z4fnYDA8/udUug/9c3ZTuI7z4XYcC9f/oqT3KEhrXdBxJDy+J8PvDof78oaCdOuKcDtfUXCNvBieq1XhuveE2+TyHz9fWRUek6sV5B/flfSCgnvC5XE2fK8/XP+BcHv86+XK8DemFNxrM+Fnrw5/51T4vddVukaOK0iDbpL0wXD/ByT9Xbhd/j3zWvido5LWh/tyMVzfFeE+ScF97NLxZeH+SNKvKjjHLg88G677rPf9PgVpk1VwbX9Z0hYFacUiBffZTLgv/eExfyP8vhTcF0fD7e5X6R57JHz/jnDd0bx9VbhNN3rHYFm4vm+F63D3+TkF1+VFBfeOVXCvnw9fu55y0XT02nD9/eG+LQ3XWQi3xeWLrrB/IfytQwrSjrcruB7cfq1QcF8dVFAmel94Tn4Sfu4qlfIKly4fDrdpVXheTobH1qUfUnzZ7kT4ey5td9x2++fRlS+uUnA/uHRWKi+rufX1h8c6qyBP/B8qpbVvV6kMucI7nu749qv8PK5VeZrgypxLVCrvuPTdVSasDtdTCPf7ZZXSfr/ce1altNSqVH4YCvfrx+G6jiq491eolOee9LbZHYcV3r/99MvlPU+rdO375Th3LawKj9VeldLlv3ef9Od/XipnuDTepUFLw+27XqW07X942zUHGGu7XRXQupGRETs21mPPxbviCun06W5vBQAAAIAkg4PSL/5iEPQ16rOflf7oj9q+Sc0yxuy21o7EvceYvk5585trfwYAAABA95w6Jd14Y3Pf/dSn2rstHUTQ1wkvvCD9+Mfd3goAAABgbjOzMCtOMz0GZ2O72oigrxO++tVubwEAAAAw983GULTrrmv8O9bOqTI/QV8nnDjR7S0AAAAAUMvtt0sf/nC3t6LjCPoAAN3RxwTSAIAa6skr+vulbMzzFuKWRf2LfyG98krj25XJSB/7WOPf6xJy3E64cu48swOY07JZaWam9ufQPv3hvOOZjHTxYnAOCoXmut9MT9f+DIB0MyZIT5YskSYnZ/e3+/uDPKRQmN3fRW333Vc+ucr/+X8m5zPZrLRggfQXfyF9/vPS179eeq/ec7t1a+PbOMcqLmnp64SR2JlSAbTKr7Hr65OGh7u3Lb3uzjtrZ0j11ID67r9f+pM/kb7xjWDdixcHGe2CBcnfyWTmXMYIYBZdc02QhkxN1f5sM/r6gvTwzjvLl2ez0i/8QpBGodLAgPTAA9Lb3tbZ34mbDOWqq6Q/+zPpd34n+PvYx2qfp7/4C+lDH6osg9eTz33+89JNNzW3r6OjjX+nS7jSO+Ghh7q9BUB6GBP0t3/ggfLgYXpaevHF7m1XLxsYkL797eB49fdL73lPqYXO94EPVA/I/MxyYEC6+mrpH//jIGP9i78IMuK/+ivpJz8JnlXkryuTCZY98kj8b0tzbuYzAC3IZOIriF55JUjPXa+NdqcL/f3SRz4SHwxQSR9vwYKgZW3rVml8vL7PDww0V8FnTGVg9m//beXnqq17wYJS98yPfUxatKi0Tf390sKFwf8HBoLl0d9zk7jcemvj295MC2GXEPR1wrPPdnsLgHTIZoPg5b/8l6A2zdX0ZbONt1L1unoKOtls7drOBQuCLjCZjHThQpDR3XFHfIvc3XdX/92PfjTIaF1m7jK3F16QfvmXgwquX/7lYNkf/VFQW+oUCtJ//s/Bv3/ndyp/u69P+jf/pvY+A2iPvr7uVrS4348L/C5fLv27nds4MBCkhVu3loKB/v7g72/+JliWVCk1l7WSPy5YEByTj30syHdrdY/MZqXf/V3pr/9auvfeoEfIwEBwrAcGpHe+U1q6tPr3v/WtoCX26quD/0cDqdHR0j658xflvnPTTcFj0/74j4MKyR//OMiL9u4NXv/xHwe/NzAQrHNgoPSsvcHBmoenzBwbXkKfm074zGekX//1bm9F+rz1raX//+QnrbfyMB6sfbLZINBo97iIf/JPpDe/Wdq0KThXFy4EGYkU/FZazp8L1KwNarwzGWloSHrttfLP1drf/v4g8x0ZkX7lV4Lul8YEr//lvwxmFv7jPw7W09cXZILVxuI98kjw/UuXglrfm24Kln/1q9L586XPffWrQWAX7eYyPS390i8FhQGXSV+6VHpvZCQYt/Hnf177GKF3ZbNBq/H3vtftLSnXaBp//fVBAfAtb5G++c10jjldsCAYi9sNly4FPTZGR6Uvfan8+Pb3lwK/duQjfX2lSqitW0tp149/HPx+dNknPiH98Iet/241mUzwF72uWhkX3ddXub53v1vatSv+vUym9vGdmQkCYnd8+vrK7yNjyrd1ZiYI1n7lV4LlxpQqardulf7pPy2l+1HZbDBc4M1vlr7znSBf+frXpZ07gwYUtw1btwbrdXna//a/BXnZpUvBNf07v1P6rBT8O/ra//cLLwR5mhQEt/77jbA22M9mvz/brLVz/m/z5s2257zzna4Ix187/xYtsvbAAWvvu6+57/f1Bf9fsMDaz37W2oGBYJ0LFlhrTO3vZzLdPwa99ueOZX9/+fI777T2Pe8J3ov73vXXW/vWt1p7++3BOqLfl6zdudPaBx6wdvHi4PXChcG5P3Ag+Lv//t691/xrxZjkayebLe3bwEBwLPzl/f2l67bW3wMPlNKgAweC1zt3WrtkSXAMFywIrnf3e9H13nlnsNydj+g52bkzWPf995cvv//+YPnOnZXbtGhRsB0HDgTXg//effcF73X7XM2FP5c+vfWt3d8W/y+bDc7/gQOla7Ybf/fdF58O1Xvv9PeX7p8DB4J7pp48oZvHPfr6zjvru4a6tZ1+WrBkSZDOuOvHpXuN/EXT1Gw2yE/uv7+Udxw4UF+Zrdaxa9dff3+Qzn/2s6W/O+8MltW7Dnce+/uD/M//bl9f+T0QPUb1XAP+veDuh/vuC45vXD49MBC87+fTAwOVeU50O1xebm3we9F71eUr0TzN5f8uX1uypP7z7N/fcd9NKq8k/S1c2NhvzwJJY9bGx0uxC+faX08GfY1eOL305xKFTKZyP9qRqbuEY8GCIGFoJJBasCC46aOFzmp/mYy17353kMAsWlR+o/sF47jCwe23B4nq295Wnqgl7Ve3Cj0uoa/3WLpAwhUUGt1ul/AvWlQ6ljt3lgIFF5xbGxzfuAxtYKD8PNx/f3mGMjBQXkCIS6APHIjPhGbzL+7YDQw0lpEvWBDs2/33V2bKd94ZHAc/+ItbbzZbnlE70aDZz4z9Y+cyev+eiO7bffeVjrurLPHPtbXB926/vXQd+OcsGhQ+8EBzhb3o33yojLnzztK9knTNd6NQ785/XKEt7i9aKG3X386dpeuyvz+4dv37JKliKbofftoyW4FAo3/9/UHevGhRqZLGBTn1fL/a/ZLJtH4d3Xln8OcX9l0a546xX4B3acPAQPBX7TqK5j333x98PpqfNBoQxFVYdepv8eLyvG3hwmD5wEBw3Vbb/2w2+Lz/Hfd/VwHr3pMq1/XZzwafq3YNRO+FuHzEVda681CtcnFgoHyb3G9EA8vo/RkN+qKi11C9/H1x58KpVra8/fZSZUUmUx609hCCvm6Yy0HfggXlhbmdO4OL+777SgW0VjKFRYvKa+FcsBD32WgBYWCgVItX6zvufb+gu2hRqVbad+BAZW2ZK0S4hGzRolJBN/qb73lPKdGrt2a51T//HCxeHOxXtCUl6c8dG/e9uJq4pGvDHcO4mlR3rbgWIXdsXcbW1xcE0O5YRxNcl/FHg4WkxP2BB9ofaBsTBPrvfneQyGezyRmkq7H1rwu/8OHXYFcrcGYyyQHQZz9bOn6u0iOu4iOpxjFaAHLnbefO8vOelNH7vxE9r9Uy3KT3/WvkgQcqCwNJf297W/K9Ve0c1fq79trqwfkNNwTH+s4723dvN5N+uoDb2lJBN3pPx+1Hs9ucVInk0lb3564JF3DFnTe3bS44OXCg1CrXroDdVY64wtyCBcG+u3TbpfsuOHXpzGc/G58n+PtUzzbORoDoKkv9Y+7fY/X2gLn99lKA0co1mclU9rTo66usrEvKd5PSjLjr2/199rOVeU/0OFQr1FfzwAPNXY8uD3UVC+7a8z/jjrWft8X1Yommy/39wbV1333Btrn77vbbywMrvweMn1/s3FlKcx94oPSeqxiJnk9XuRR3bqKBdPS4x/Uu8fMcVwEczd+dpIrjdqtVkZyUH7hj3EygOYsI+rqhkZYol2G4BMPVIDzwQKnGrJWCba1EzE/s+/pKBU8/sUzK0BvdjmoJyv33Bwm6Cy79GiT3nt9SFxfgLFhQCkjiap2SMoBoYcHVMEUzD7cdcYm+24ekz9RzDuIyOmPiz39cy2W0tjIu43GJbjTxjh7P6HVRK+OulZAmdcuolYFXUy2BbuTPb32OFmKT7r3bb4/P7KL74l+HSdu6YEFwPqMBkKvkSCrA7NwZ3FOf/Wz145V0TP1rNun7cYF8u7jjUyswca2Q1d6v1UKQ9OeCkNtvL1/+znfGV1600krljmMzXQcXLKi8rlzhzZ1/1zrljoO7Zz/72SD4aiQfiQsi/dbduOvRBXPZbLB//f3xhUP/8/ffXwoIBwYq06H3vKfy3N93X2WQdd99pcK33wri39P+7zaSxvh5U9z5X7iw8S6KV19d/X1XEeTuz3q6K0bTf7etriLXr8x1++Xyguh+1bpWstlS0FztOm2mgJxU3oh2O6x2HKoFF7W+6wKPgYHKdCH69853lu+rn177f3feWT1/iFZy+ulyXCukC4xq5be+aDknWjasFWg1et8k3fPNVBa2W7Xfccc/WqHhX9s9bE4GfZLulbRb0lOSfrnaZ3sy6Ku3MGpMeWCVVDCulvD09QXvxxV4XK2b64/tuk9EEw+XGbi/aELiJxbVuh+4Lo5xgWYjNTdxN2Q0AIsek0ymvDuAW0et2iX32aTEN7o82l3R1XZHA5nPfjZoLYoW7vzXxpSO5cKFQcYQzXxd4u5aym6/Pbmm19ryQrqf+flBW9L3/N91x67esRG1alej13dcjWAzCeqBA6VaUP86vP32UiZc7V68/fb42v6kihtX2Gn0WnbXTVJXV3cs4gryjdaYzyV+wT/pHH32s8HxcwXBaC216z1w333J68lkgnN9552lVtykVqqBgfiCq1+wa6RFIJutDCAbrRiK6w6VVKiqlpbV01sjm01uYY67Z/1taaaVJXqMFy4sdWNz77lAbuHC0mdda5VfAF60qLxrYSMtPUnbFk3b4yohXeHcpbfR69AFbm7cbDQPffe7S9d09HppRLRVJ6lyLXrs3ba7/N0dPzc8wm8d8ntquMDRb/mNuzYbLcy7e8TPD+tJd/0KkbiAv5bo9RutjIsGw3EVCn6XzVqtVvUcl7gWXJcX1HNMo/lttHKxry+5Qn6uajV4dPmSf59G0+AeNeeCPknLJT0taSD8915JA0mf78mgz9pSotXXFySc2WxlTWHSRRRNeKIFhGgrj58RL1pk7RVXlDL2uIzZ1cb6CXe0YBNNsKPdHF0mcOedpf7dLnj0C7h+AbbV4xnNxGplCI1kAPXWTMWtM2nc1JIl5UGnqxn1CyhJBYdod6hmE7B6v+sXqptJ3KoFJ0kF0Wa74ST9flKrlXvP3Y9Jhep6gj4/WGj02LhrxgU50ZaIategXyvfbIDcy9w+RsdC+q1FcYXvuOssWqjxuyHGSWrpj/tNv1t6Uuui64YVrUy4/vrS+y7dfOc7g3VUG6/pdxmu91jWKuA/8EDy/eC3BtVKE+OOUTsqcuptEYm2rrj8rNVtcKqlUUkVWf41Em0l99cXrURqtaAa1cj6XMWHa3GtNv69WtAfd66Szl+9+1CrN4Kv1Twl6XqO6y6ZlKbEXQutiFbIRsdHNro/0coxv5IrDVq53qLfd3m03/OM7p1tD/o+Julz3usdkrYmfb5ngz4nmvDW0/Ug7qKNJjRxGeMDD1TO7ua3JlZbfyP7Ef3tuIS23RlY0j5XyxDaGVTU2o5q3UmTzlW1IHu2E5ZWE0q3jrjgJOk8tOM3G+G3GET/XGuGvy9xBfBGMlz/d1u9Pzp1LfcaV/h0x9sfq1jPMTtwoFQpFg3iqn2nVqVEtDLH3bvVWuz833UBX9xftFXdD2g7Wcg4cKC8S6Kb2Gm2r+16t7Vad6xa441a+d1aaVQj6Zj/2V5quY+ex2qtSNWObdz1MJtpV7vysaT8ulv8FtxW8w13jJptDe11rV5vSfdCOyq0ZsFcDPr+maR/6L3+XUkfi3zmNySNSRpbu3Zt+49ap9VbeGkmoYnrttNowt2o2S6812s2t6taTehc0Y5rolom08j4g07wMzvXrblWS7Gb7cxvVW40I2lXQWSuXleN8sdHtaO2vtFKrbj1JI1l81vIq005nhTwuZ4b3dLK+Cdre+e67GQ6UmvdjRYyeyGIiGrXeUwKwGfzGunF49stScc+zceo1eutnkrAHq54rRb0meD93mKM+W1Jr1hrvxS+/pykv7PW/kXc50dGRuzY2NhsbmJvu+WW4GGjzlvfKv3d33X+d194ofKhp72gG9vVq8diNrzwQvAwdWuDh6ju2VN6GGovHBN/O6TgweJS9Qe0vvBC8Ll/+2+DffL3q5nfbXb/e+UYdlrSNdToOtpxrNx6rr22/OHD/nXtttXa0kOWs9kgHXa/fcMN0osvxv/Gzp3Shz7U/Da2qtVjNV+uyyTtuF57QbvvGX898/0a6ab5eOw7kabNkfvcGLPbWjsS+16PBn33SRqy1v7f4es/kfRn1tqn4j5P0BfjllukZ5+V3vEO6Zlnur01mG/Smsmkdb96US8e66RtilYkJG23C/wyGekXf1FasUK6557uBnxoj168XgG01xy4z+di0LdG0l9Jeq+kxZK+I+k91tpC3OcJ+gAAAADMZ9WCvr7Z3ph6WGuPGGP+VNITkjKSficp4AMAAAAAJOvJoE+SrLU7FMzaCQAAAABoUqbbGwAAAAAA6ByCPgAAAABIMYI+AAAAAEgxgj4AAAAASDGCPgAAAABIMYI+AAAAAEgxgj4AAAAASDGCPgAAAABIMYI+AAAAAEgxgj4AAAAASDGCPgAAAABIMYI+AAAAAEgxgj4AAAAASDGCPgAAAABIMYI+AAAAAEgxgj4AAAAASDGCPgAAAABIMYI+AAAAAEgxgj4AAAAASDFjre32NrTMGHNc0kS3tyPGlZJOdHsj0PO4TlAPrhPUg+sE9eA6QT24TuaeYWvtqrg3UhH09SpjzJi1dqTb24HexnWCenCdoB5cJ6gH1wnqwXWSLnTvBAAAAIAUI+gDAAAAgBQj6OusL3R7AzAncJ2gHlwnqAfXCerBdYJ6cJ2kCGP6AAAAACDFaOkDAAAAgBQj6AM6wBizzBizttvbAQAAABD0dYgx5l5jzG5jzFPGmF/u9vZgdhhjBo0xfyVpXNI2b/kfGGOeNsaMGmNuCpf1G2O+GF4jf2uMGQqXrzDGfMMY86Qx5mvGmCXh8rXGmO+Hy79gjMl2Yx/RGmNM1hjzR8aYR8M04p+Fy/+FMWbMGPMjY8x7vM+3fO1g7jHGLDbGfDO8539gjHl7uJy0BBWMMQuNMfuNMf8ifM11ggrGmENh3vOoMeYPwmVcK/MEQV8HGGOWS/qnkt4j6YOS/o0xZqC7W4VZMi3p9yT9tltgjPmgpOXW2lslfVbSfwjf+jVJz1tr3yVph6R/HS7/LUkPW2vfLelJSZ8Jl/++pM+Fyy9K+tUO7gc6p0/St62175d0q6SPG2NuU5BWbJH0MUn/UWrrtYO555Kkj1lrPyDpX0r6bdISVPF/StolkeegqvPW2veHf/+ca2V+IejrjA9J+htr7UVr7aSkHygo3CHlrLVnrLXPRhbfKenPw/d3S1prjMn4yyX9taSfCf/985K+Gv77wfC1JG201v4gZjnmkDBd+Nvw3zOSXpT0LklftIGXJeWNMW9S+64dzDHW2mlr7fnw5VslPSPSEsQIW4GvlvT9cNGd4jpBfe4U18q8QdDXGddKOuy9flVBgoz5KXo9HJOUk7RawbUha+20JBO+32ft/7+9uwmxKQwDOP5/yhjZMDKIZmWslBpWUtazslLSKJ9RkpSmlOVsRLKQkiQ1FpSkbEasKRsbKcVCiCmf2fl6LM5r3BmujXtozv3/6nTPeW+dzuk8Pd3nnOc9Nz+V9VdAf0T0AW9a9mFMNUBELAP6aZ8z/jp2ajt41S4iRiPiMbANOIu5RDOUH+jHaOkuwThRe29Lu/iNiFiNsdJVLPrqMRf42rL9rSzqTu3iYU5O/8+UL+Vzqhe+fP/lD/vQLBUR84Fxqlbwdte3E7GjWSozT2TmIFW77zjmEv3qIHAlM1+3jBkn+q3M3JiZG4AxqidyxkoXseirxytgecv2CuD5fzoW/X8z46EPeEvVwtcP1cs9+JlU88ck6IhYCkwCr4ElLfswpmaxMsf3MnC8tAO3yxmdiB3Ncpl5FViFuUS/2gJsjYgJ4DCwh6od2DhRW5l5j2resDmli1j01eMWsLm8/WgBMESZYK2uNEHVnkVErAMelTtkU+NU/fO3y/odYFNZ3wZcL3O/XkTE2tbx2o9cHRcRc4BLwLnMvFWGJ4CR8v0A0JOZk3Qgduo8F9UnIgYiYl5ZH6Ka+2ku0TSZuT4zhzNzGDgJnAeOYJxohojoLR0mRMRKqpZNc0oXielPb9UpEbEP2EVVWB/98eIGNVtELAKuUfWz9wDPgN3AKLCG6s7a9sx8WpLvRaqe+nfASGa+L3fXxoGFwBNgZ2Z+iohB4ALQC9zNzEP/8NTUISU3jAEPW4ZHgL38nPy+PzPvlzuqZ/jL2Kn/rNRpEbEBOA18KMsB4CUdiAdzSTNFxA5gMXAK40QzlOt8E/gIfKZ6MvwAY6VrWPRJkiRJUoPZ3ilJkiRJDWbRJ0mSJEkNZtEnSZIkSQ1m0SdJkiRJDWbRJ0mSJEkNZtEnSZIkSQ1m0SdJkiRJDWbRJ0mSJEkNZtEnSZIkSQ32HeJCANXLI3xyAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cls = energy_clusters.get_cluster()\n",
    "cls_data = pd.DataFrame(data)\n",
    "cls_data = pd.merge(cls_data, cls, left_index=True, right_index=True)\n",
    "cls_data=cls_data.reset_index()\n",
    "color = [\"red\",\"pink\",\"orange\",\"gray\"]\n",
    "plt.figure(figsize=(15,10))\n",
    "for i in range(4):\n",
    "    plt.scatter(cls_data.loc[cls_data['0_y']==i,'index'], cls_data.loc[cls_data['0_y']==i,5] #就是取出y_pred是0，1，2，3的那一簇的X\n",
    "                ,marker='o' #点的形状\n",
    "                ,s=8 #点的大小\n",
    "                ,c=color[i]\n",
    "                )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdec46da",
   "metadata": {},
   "source": [
    "每个用户的用电曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 383,
   "id": "faea7aa5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "sns.lineplot(x=cls_data.index, y=5, hue='0_y', data=cls_data)\n",
    "plt.ylabel('年均用电量')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  },
  "vscode": {
   "interpreter": {
    "hash": "865d8b2eb28e274047ba64063dfb6a2aabf0dfec4905d304d7a76618dae6fdd4"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
